LTS QA

In today’s rapidly evolving digital landscape, safeguarding software integrity is a top priority. White box penetration testing is a crucial cornerstone in the proactive defense strategy against emerging cyber threats. This detailed testing approach offers a unique viewpoint, much like a hacker’s perspective from inside the system, enabling a thorough exploration of potential vulnerabilities deeply embedded within the software. 

As the digital world continues to expand and evolve, so do the sophisticated techniques of cyber attackers, white box penetration testing serves as a crucial tool in staying ahead of these threats by revealing weaknesses in the system’s core, allowing for proactive reinforcement of security measures.

Understanding the pivotal role of this method within software quality assurance is essential, as it not only identifies existing vulnerabilities but empowers organizations to proactively strengthen their software, fostering resilience against potential breaches and cyber-attacks.

 

What Is White Box Penetration Testing?

White box penetration testing definition, referred to as clear box or structural testing, is a technique that grants the tester access to the internal structure of the system to replicate a hacker’s actions and uncover potential vulnerabilities. This method provides a comprehensive understanding of the application, identifying all possible entry points into the system.

White box pentest is frequently employed to examine a system’s essential parts, particularly by companies that develop their software products, or integrate multiple applications. It is a method to evaluate a system’s security by assessing its capability to withstand various real-time attacks.

 

Benefits of White Box Penetration Testing

An efficient white box penetration test helps avoid the issues, errors, and oversights that can leave your businesses vulnerable to hackers. Let’s explore more benefits of white-box penetration testing:

• Comprehensive oversights of possible issues: White box penetration testing offers the most comprehensive analysis of internal and external vulnerabilities from the internal point of view, which is not available to typical attackers.
• Early detection: White box penetration testing is integrated into the early development stages, when there is no user interface, and even before the software application is available to users, which enables detecting the vulnerabilities at a very early stage.
• Extensive testing coverage: White box penetration testing can identify weaknesses in areas that are unreachable for black box testing, for instance, an app’s source code, design, and business logic.
• Precise identification of weaknesses: Since testers have detailed knowledge of the internal workings of the system, they can pinpoint specific weaknesses, potential security gaps, and flaws in the code logic. This level of detail often leads to more accurate identification of vulnerabilities.

Disadvantages of White Box Testing

Despite all the appealing advantages, white box penetration testing shows some drawbacks in certain situations:

• High programming language requirements: Implementing white-box penetration testing involves internal network testing, which requires the testers to be familiar with critical programming tasks, like performing port scanning, SQL injection, and common attacks. By this, they will have a better understanding of the potential access points.
• Limited real-world simulation: White box testing operates with complete knowledge of the system, which doesn’t accurately replicate real-world attack scenarios where attackers have limited or no knowledge. This approach might overlook vulnerabilities that would be apparent to external attackers working with less information.
• Risk of biased testing: Testers, armed with complete system details, might inadvertently focus on known weaknesses or areas they are more familiar with, potentially overlooking other vulnerabilities that could be exploited by attackers with different perspectives.

 

Black Box, Grey Box and White Box Penetration Testing Differences

Black box, grey box and white box testing are all types of penetration testing – the practice of testing a computer system, network, or web app to find issues, errors, and vulnerabilities that an attacker could exploit. 

 

To help you distinguish between black box, grey box and white box penetration testing, understand the benefits and limitations of each type, and when to apply it to get the best results, we have summarized it in the following comparison table:

Aspects	Black box penetration testing	Grey box penetration testing	White box penetration testing
Level of knowledge requirement	Require little or no knowledge of infrastructure and network	Require basic knowledge of the internal codebase, architecture, and infrastructure	Allow complete access to knowledge about the system’s infrastructure, codebase, and network
Level of programming language requirement	Require no syntactic knowledge of the programming language	Require a basic comprehension of the programming language	Require high and professional understanding of programming language
Standard techniques	Boundary value analysis, Graph-Based testing, Equivalence partitioning, etc	Regression testing, Pattern testing, Matrix testing, Orthogonal array testing, etc	Decision coverage, Path testing, Branch testing, Statement coverage, etc
Advantages	– Mimics real-world attacks – Provides an outsider’s perspective – Encourages creative problem-solving	– Balances realism and deeper insights – Enables access to some internal system knowledge – Optimize time and resources	– Understands thoroughly of the system’s internals – Delivers comprehensive coverage of system security – Pinpoints vulnerabilities in code and architecture
Disadvantages	– Limited insight into internal structures – Incomplete view of vulnerabilities – Possible overlook of certain critical vulnerabilities	– Restricted insight compared to White Box – Dependent on available information – Possible miss of certain system areas	– Time-consuming due to in-depth analysis – Costly due to skilled personnel and time- Prone to false positives if not done carefully
When to use	– Simulating external threats – Testing overall security posture – Assessing response to unknown attackers	– Balancing depth and efficiency – Targeted testing with some internal insights – Limited access but need for deeper insight	– Assessing specific system components – Analyzing code, architecture, and design – Identifying and fixing intricate flaws

 

The selection of Black Box, Grey Box, or White Box Penetration Testing depends on the level of internal knowledge required, the depth of the assessment needed, and the specific objectives of your security testing rpojects. It’s often beneficial to employ a combination of these methodologies for a comprehensive security assessment based on the unique needs of the system or software being evaluated.

 

White Box Penetration Testing Techniques

When it comes to software security testing, security testing white box techniques review source code (the internal structure of the software application) to detect gaps that can make an application vulnerable to cybersecurity threats.

One of the main goals of white box penetration testing is to cover the complete source code as extensively as possible. Three main types of techniques for use in white box penetration testing include Path coverage, Statement coverage, and Branch coverage.

Path coverage

This white box test methodology pays attention to all the paths. The path is a flow of execution that follows a set of instructions. The path coverage examines all possible paths of the software and ensures each path is traversed at least once. The path coverage is far more powerful than the branch coverage and is useful for testing complicated builds.

 

Statement coverage

Statement methodology checks if each functionality was tested one time. A statement indicates a functionality or set of actions for the application to decode depending on its programming language. 

An executable statement is when the statement is put together and transformed into an object code, which will subsequently execute the action it was designed for. It helps to uncover unused or missing statements and branches as well as leftover dead codes.

The statement coverage evaluates if each line of code is executed at least once and helps find unnecessary or missing lines.

 

Branch coverage

A branch is one of many execution paths that the code can take after processing a decision statement like an if statement. This method is to confirm that all branch codes are tested.

The branch coverage is tested to check whether all branches in a codebase are exercised by tests and no branch leads to abnormal behavior of the application. It maps the code into branches of conditional logic and ensures that all branches are covered by unit tests.

One should ascertain that all codes have been launched at least once.

 

Common White Box Penetration Testing Tools

Several common tools/libraries employed in white-box penetration testing include:

1. Metasploit: Penetration testers utilize Metasploit to create and authenticate exploit code before deploying it in real-world scenarios. It’s instrumental for network security testing or remote system intrusion.
2. Nmap: As an open-source network administration tool, Nmap monitors network connections and scans extensive networks, aiding in host and service auditing as well as intrusion detection. It offers packet-level and scan-level analysis and is freely available for download.
3. PyTest: Pytest, a comprehensive Python testing tool, facilitates writing more efficient programs, supporting test-driven development (TDD) and behavior-driven development (BDD).
4. NUnit: NUnit is an open-source unit testing framework beneficial for the .NET Framework and Mono, aiding in writing better code and reducing application bugs.
5. John the Ripper: This fast password cracker identifies weak Unix passwords and is compatible with various operating systems such as Unix, Windows, DOS, BeOS, and OpenVMS. John the Ripper supports multiple password hash types commonly found in Unix systems and other patches contributed by users.
6. Wireshark: Functioning as a network traffic analyzer, Wireshark enables monitoring and analyzing traffic within system networks. It is open-source and widely recognized as the foremost network analyzer globally, primarily used by network administrators and professionals to troubleshoot network and system performance issues and filter various network protocols.

The tools employed in white-box penetration testing are similar to those used in other penetration tests, but the methodology for employing these tools differs significantly.

Essential White Box Penetration Testing Steps

A process of software white box penetration testing comprises the following steps:

Source code review

The initial step is understanding the internal structure and functionality of a target software application. This crucial step requires a test engineer to review thoroughly the software’s source code, and understand clearly how it works in order to set the foundation for designing test cases that will help encounter security weaknesses.

 

Select the testing areas

After understanding completely the software’s internal structure and how it functions, the next step is determining the areas that need to be tested. 

As the test aims to encompass every potential scenario for running code systematically, it proves more effective to explore the numerous possibilities within a smaller area rather than a larger one, as the latter wouldn’t ensure the same comprehensive coverage.

Covering a vast area is feasible, yet it demands significant effort, resources, and labor for test coverage. Consequently, it’s not recommended to execute this extensive coverage only on demand. For instance, it becomes essential in situations where it’s crucial to safeguard every aspect of the system; in such cases, it would be deemed necessary.

 

Code & flowchart identification

This step adds a structured approach to the white box penetration testing by visually mapping the code execution process, facilitating a more organized and systematic analysis of the system’s functionalities.

• Identify potential code lines: Thoroughly examine the system and identify all possible code segments associated with the functionalities or aspects under test. This involves a comprehensive review of the codebase, focusing on critical areas that could be potential sources of vulnerabilities.
• Create a flow chart: Outline the flow of the identified code segments. Create a flow chart or diagram to represent the flow of code execution, including input points, processing stages, and output results.
• Output tracing: Document and trace the output of each code segment within the flow chart. This helps in understanding how inputs are processed and how outputs are generated, aiding in the identification of potential vulnerabilities and understanding the system’s behavior.

 

Design test cases

Designing test cases is a pivotal phase in white box penetration testing, involving the creation of detailed scenarios for every identified code segment and system functionality. 

Each test case outlines potential vulnerabilities, failure points, and specific testing procedures. It includes boundary testing, attack scenario simulations, and meticulous recording of testing outcomes to comprehensively evaluate the system’s security posture and ensure a systematic approach to identifying and addressing vulnerabilities.

 

Execute testing 

The execution phase in white box security testing involves putting the devised plans into action, rigorously conducting tests according to the outlined strategies, and repeatedly iterating through the testing process until all identified systems are thoroughly examined, leaving no vulnerabilities unchecked.

This phase includes comprehensive testing, meticulous documentation of findings, validation of vulnerabilities, and continual refinement of testing procedures to ensure the system’s robust security against potential threats.

 

Reporting 

Compile a detailed report that includes identified vulnerabilities, their potential impact, and recommendations for mitigation. This report should prioritize vulnerabilities based on their severity and guide how to address them.

 

Continuous improvement

Security is an ongoing process. Continuous monitoring, regular security assessments, and improvement in policies and practices are essential to maintain a robust security posture.

 

White Box Penetration Testing by LQA

Enhancing cybersecurity testing involves engaging a specialized security firm to assess your business’s vulnerabilities and deliver a detailed report with recommended solutions, a crucial step in preventing cyber attacks.

Having more than 7 years of experience, and as the pioneering independent software QA in Vietnam, LQA stands out as a prominent IT quality and security assurance firm, offering a complete range of penetration testing services to fortify businesses against security threats.

Alongside white box penetration testing services, LQA provides comprehensive software testing services including white box, black box, web application, mobile application, API, manual, and automation testing services.

At LQA, we maintain up-to-date expertise on the latest threats, attacks, and vulnerabilities, employing industry-leading tools to conduct comprehensive penetration tests.

Key features of LQA’s white box cyber security solution:

• Comprehensive software QA solutions covering consulting, planning, execution, and ongoing support.
• Ensured bug rate lower than 3% for devices, mobile, and web applications.
• Rapid delivery facilitated by a diverse pool of proficient testers.
• Optimal price-to-quality ratio, leveraging cost benefits and expertise of Vietnamese IT human resources.
• Tailored solutions based on industry-specific experience.
• Maximum security ensured through a Non-disclosure Agreement (NDA) and best security practices during database access.

Connect with LQA’s experts to safeguard your data and assets from potential hackers today!

 

Frequently Asked Questions about Haptic Feedback

1. What is white box penetration testing?

White box penetration testing is a comprehensive security assessment method where testers have complete access to the internal architecture, design, and system details of the target. In this approach, the tester possesses full knowledge of the system’s infrastructure, including source code, network diagrams, and system configurations.

2. What is a white box penetration testing example?

An example of a white box test could involve analyzing the source code of a web application to identify vulnerabilities. Testers would scrutinize the code, look for potential security flaws, and examine the database structure and application logic to uncover weaknesses in the system.

3. What are black box grey box and white box penetration testing?

Black box, grey box, and white box penetration testing are distinct approaches used in security assessments to evaluate the vulnerabilities of a system. Here are the brief definitions of each type of penetration testing:

• Black box penetration testing: A security testing method where testers have no prior knowledge of the system. They approach it as an external hacker would, without any internal information about the system’s architecture or design.
• Grey box penetration testing: A security testing method where testers have partial knowledge of the system, such as limited access or some details about the internal architecture. This approach combines elements of both white and black box testing.
• White box penetration testing: A security testing method where testers have complete access to the internal architecture, design, and system details of the target. Testers possess full knowledge of the system’s infrastructure, including source code, network diagrams, and system configurations.

4. What is the difference between black box and white box penetration testing?

The main difference between black box vs white box penetration testing lies in the level of information and access the testers have. White box testing involves complete access to the internal structure, code, and system design. On the other hand, black box testing operates without any knowledge of the internal system; testers approach it as an external attacker.

5. What is more costly black box or white box penetration testing?

Typically, white box penetration testing is more resource-intensive and thus can be more costly. It demands a higher level of expertise, time, and resources due to the need for in-depth knowledge of the system’s internal workings, including analysis and evaluation of code, architecture, and configurations.

6. What is the white box penetration testing methodology?

White box penetration testing is not just a single test but a methodology involving a structured and systematic approach. It involves various steps such as reconnaissance, scanning, vulnerability assessment, exploitation, and reporting. The white box security testing methodologies focus on a deep dive into the internal workings of a system to identify and mitigate potential vulnerabilities and security risks. White box testing is an essential part of a comprehensive security assessment, ensuring a thorough evaluation of system security from an insider’s perspective, and it plays a crucial role in strengthening the overall security posture of an organization’s infrastructure.

 

Final Thoughts About Whitebox Penetration Test

White box penetration testing serves as an effective method to strengthen software security. The level of complexity varies based on the application under assessment. Evaluating a small application that conducts straightforward operations is a swift process, often taking only a few minutes. However, larger applications necessitate significantly more time, ranging from days to weeks or even months.

Conducting these tests is crucial during the software development phase, both after its initial writing and following any subsequent modifications. Integrating white box penetration testing into your security strategy is pivotal, as it aids in preventing mistakes and oversights that could potentially expose your company to cyber threats.

If you are looking for experts in conducting white box testing for your IT environment or apps to check if they’re secure, don’t hesitate to contact LQA’s security testing team.

 

The riddle of how to nurture, recruit and retain IT talents is the universal problem that HR departments face every day. As in the IT industry, 80% of the candidates are passive candidates, meaning that they’re already occupied. The process of planting the seed of job switching to attracting those candidates to apply to your company is a long and demanding journey. In this journey, for every step of nurturing, recruiting and retaining poses different challenges; fortunately, these can be easily tackled, thanks to the following solutions:

1. Build a strong employer brand
2. Employee referral program
3. Competitive benefit and compensation program (what motives your staff?)
4. Broaden your recruitment sources (institution)
5. Proper investment in HR Campaign
6. Remote Staffing
7. IT Outsourcing

 

1. Build a strong employer brand

72% of recruiting leaders worldwide agreed that employer brand has a significant impact on hiring, and 75% of those who are looking for a job often take employer brand into consideration. Also, 49% of LinkedIn users following official social media accounts of tech firms to watch our for job openings.

Building a strong employer brand is not something that you can do overnight but a long-term investment, both for business development and recruitment attraction. Still, it is important for one to “imprint” a good impression of your brand. These impressions would range from modern workplace, young and dynamic work culture, transparent policies, etc. Especially in the IT industry, candidates have a wider range of choices, hence they always go for the company with outstanding features of flexibility, scalability, etc.

 

 

The real question here is that “How does your employer brand stand out?” The most popular and common channel is social media. By leveraging your image on platforms such as LinkedIn, Facebook, Instagram, you’ve already highlighted the robust work culture and friendly environment. The choice of what image you want to put on to attract candidates lies in your hands. It could be young and dynamic, or friendly, or professional, it’s up to you.

To deliver the image of your employer brand as an IT recruitment solution, you can go with media sharing, company events, job development opportunities, etc. Through these, potential candidates will first capture the essence of the workplace and then engage more in the activities of your company.

In terms of career development, it’s best that you set up and organize technical events such as host meetups, workshops, and hackathons to revamp competition within the business.

Also read: Top 7 challenges in IT recruitment

 

2. Employee Referral Program

Employee Referral Program has long been an effective IT recruitment strategy exploited by many businesses. In this program, employers encourage their employees to refer qualified candidates with rewards.

 

 

This strategy has proven its effectiveness through multiple analyses indicating that employee-referred staff tends to outperform the nonemployee-referred ones. Alongside these performance-related metrics, an employee referral program also helps businesses hire talents with suitable backgrounds and avoid any unwanted characteristics. Plus, as the information about the job openings is shared through the employees’ network, more candidates can get access to the information at a quicker pace, hence boosting the recruitment process.

With a reasonable reward, an employee referral program is considered a cost-effective way to tap into a large and qualified talent pool of passive job seekers.

 

3. Competitive benefit and compensation program

Each job position in different companies offers different pros and cons, and there is no one-size-fits-all vacancy that can meet all the requirements of the candidates. As a result, you should research the factors that motivate them, in which benefit and compensation are two factors contributing to a successful IT hiring process.

The most common priority recently is the remote working conditions. The candidates also put an emphasis on how they can balance out their work life and personal interests. You can also understand this as they are willing to move out of the suburban areas if they can work remotely.

 

 

Another fraction is the reference for internal development, meaning more training, technical courses and on-job guide, etc.

Concerning the finance factors, although the salary and other financial compensation policies might sound very compelling, the social and mental benefits top at the priority of what tech engineers look for in their jobs.

Due to the shortage of IT talents, tech engineers are spoilt for choices of the company they can work for. To make your business stand out in this very competitive environment, businesses are compelled to produce an impressive benefit and compensation program.

 

4. Use different platforms and sources for acquiring talents

Recruiting is not just about posting to job and waiting for candidates to flock to you. This is never an effective way for you to find the best candidates. Indeed, it requires one to employ multi-platform recruitment to search for as many applications as possible.

As it is shown with the following statistics, although job listing and social business platform is quite popular within recruitment community, more than 71% of the talents come from employee referrals and internal hiring, 65% are from LinkedIn and 56% are from Indeed.

These sources of applications and candidates have proven its success with quite prominent numbers, but the outlook for the IT recruitment process can be even better if you employ some of the following methods:

• Hackathons/coding competitions: By organizing these “playgrounds” for developers/testers, you expose your employer brand to a small society of IT worker community, hence raising the chance of being considered when they have a plan for changing jobs. Through these competitions, you also get access to the personal contact address of the candidates, which can be used for later candidate nurturing.
• IT training institutions: Partnership with universities and colleges with IT majoring can give you early access to a large and dynamic talent pool. This can ensure high-quality candidates thanks to the systematic and intensive training during their tertiary education.
• Certificate providing institutions: organizers for IT certificate provision have contact points of the qualified IT candidates in different fields that can assist the mass recruitment process.

Talent acquisition does not always mean the recruitment from direct sources of candidates who will later on work as in-house staff. Instead, many international tech giants have switched their approach to staff augmentation or third-party recruitment services. With this rather new approach, your company would benefit from a bigger talent pool with candidates specialized and expertise in one particular domain or technology.

5. Proper investment in HR Campaign

As talent shortage becoming an alarming problem in the IT industry with 69% of companies globally report talent shortages, tech enterprises now place heavy emphasis on Human Resources and IT Recruitment. HR department now holds greater responsibilities and priorities amid the pandemic, requiring decision-makers to take more measures to improve recruitment campaigns. As the competition among tech companies gets more and more serious, it is urgent to employ a proper investment in HR campaigns to stand out in the market.

 

Here are some critical channels to improve HR campaign’s performance:

– Signing Bonus. This can be the leveraging factor that can boost the recruitment process. One-month salary bonus or even more is exactly what one might expect to receive from their employers. This is not only a welcoming gift for the staff but also a promoting point for the company’s image.

– Advertising on multiple recruitment platforms. With a reasonable budget allocation, HR leaders can arrange ads to attract more candidates. Each recruitment platform has its pros and cons, which requires decision makers to do their research and try them out before sticking to any particular platform.

– Linkedin Talent Premium. With this all-encompassing hiring platform for talent professionals, a recruiter can find, connect with, and manage the people you want to be on your team. With a small cost, you can work efficiently and get access to a large talent pool with tech engineers from all over the world.

– Recruitment landing page. A well-designed recruitment landing page is crucial in creating a good impression towards IT talents. With subsequent information about opening jobs, plus nice content and picture layouts, the candidate can sense the professionalism of your business.

6. Remote Staffing

Remote staffing is an trending solution for IT recruitment. For some enterprises, the burden for IT recruitment takes up too much of their resources, not to mention the following additional cost of onboard employees. One way to approach these issues is to implement remote staffing and hybrid work.

With remote staffing, every operation and activity is executed on online platforms, which can eventually save up operational and infrastructure costs.

For the recruitment process, remote staffing can refer to the online operation of the recruitment team. Every step of the process is done virtually with a variety of platforms, including LinkedIn, Facebook, etc.

7. IT Outsourcing

IT Outsourcing is a service that has long been on the market with a relatively steady growth rate. As in the IT Services Outsourcing Market Size, Industry Report, 2020-2027 of Grand View Research, the global IT services outsourcing market is projected to grow at USD 520.74 billion in 2019. The annual growth rate (CAGR) from the phase from 2020 to 2027 is expected to be 7.7%.

IT Outsourcing is not a new approach in IT recruitment. In fact, its development over the years has proven its capability to thrive as an independent sector.
With IT Outsourcing, you can:

• Cut back costs by approximately 50%
• Halt employee turnover
• Hire experienced experts from BPO
• Have a low rate of burnout

The burden of IT recruitment can’t be solved overnight. Instead, it requires careful observation to decide on the optimal solution for a business to adopt. These 7 above strategies are popular Solutions for IT Recruitment but they are not the one-size-fits-all solution for all companies. One should consider their situations to find the best way out for them.

 

About Lotus QA

Lotus QA, as part of Lotus Group, is an emerging global IT firm specializing in providing the best technology services to the world. We have a comprehensive talent pool of top-notch IT engineers to offer you the most cost-effective HR solutions. We can ramp up a team for you in just 2 to 3 weeks and conduct interviews for you to choose your own team members. We provide a flexible approach for any of your requests.

If you’re looking for the Solutions for IT Recruitment, contact LQA for the 24/7 consultation of the HR market. We can help with this problem in no time.

• Website: https://www.lotus-qa.com/
• Tel: (+84) 24-6660-7474
• Fanpage: https://www.facebook.com/LotusQualityAssurance

 

One of the most popular use cases of AI and Data Annotation is Autonomous Car. The idea of Autonomous Cars (or Self-Driving Cars) has always been a fascinating field for exploitation, even in entertainment or actual transportation. 

This was once just a fictional outlook, but with the evolution of information technology and the technical knowledge obtained over the years, autonomous cars are now possible.

 

Perhaps the most famous implementation of AI and Data Annotation in Autonomous Cars is Tesla Autopilot, which enables your car to steer, accelerate and brake automatically within its lane under your active supervision, assisting with the most burdensome parts of driving. 

However, Tesla Autopilot has only been confirmed of success in several Western countries. The real question here is that: “Can Tesla Autopilot be used in highly congested roads of South-East Asia countries?”

 

The role of Data Annotation in AI-Powered Autonomous Cars

Artificial Intelligence (AI) is the leading trend of Industry 4.0, there’s no denying that. Big words and the “visionary” outlook of AI in everyday life are really fascinating, but the actual implementation of this is often overlooked. 

In fact, the beginning of AI implementation started off years ago with the foundation of a virtual assistant, which we often see in fictional blockbuster movies. In these movies, the world is dominated by machines and automation. Especially, vehicles such as cars, ships and planes are well taken care of thanks to an AI-Powered Controlling System.

With the innovation of multiple aspects of AI Development, many of the above have become true, including the success in Autonomous/Self-Driving Cars.

 

Training data with high accuracy

The two important features of a self-driving car are hardware and software. For an autonomous car to function properly, it is required to sense the surrounding environment and navigate objects without human intervention.

The hardware keeps the car running on the roads. Besides, the hardware of an autonomous car also contains cameras, heat sensors or anything else that could detect the presence of objects/humans.

The software is perhaps the standing point of this, in which it has machine learning algorithms that have been trained. 

 

Labeled datasets play an important role as the data input for the aforementioned learning algorithms. Once annotated, these datasets will enrich the “learning ability” of AI software, hence improving the adaptability of the vehicles.

 

With high accuracy of the labeled datasets, the algorithm’s performance will be better. The poor-performing data annotation can lead to possible errors during a driving experience, which can be really dangerous.

 

Enhanced Experience for End-users

Who wouldn’t pay for the top-notch experience? Take Tesla as your example. Tesla models are the standard, the benchmark that people unconsciously set for other autonomous vehicle brands. From their designs to how the Autopilot handles self-driving experience, they are combined to create a sense of not only class but also safety.

How Tesla designs their cars is a different story. What really matters for the sake of their customers is safety.

Leaving everything for “the machine” might be frightening at first, but Tesla also guarantees that through many of the experiments and versions of the AI software. In fact, it was proven that Tesla Autopilot can easily run on highway roads of multiple Western countries.

 

We might have seen the footage of how Tesla Autopilot Model X was defeated on the highly congested roads of Vietnam. However, we have to take a look back at the scenario in which we need an autonomous car the most. 

The answer here is the freeway and highway. And Tesla can do very well on these roads.

The role of data annotation in this case is that through the high-quality annotated datasets, the machine is trained with high frequency, therefore securing safety for passengers.

 

The future of autonomous vehicles

We don’t simply jump from No Driving Automation to Full Driving Automation. In fact, we are barely at Level 3, which is Conditional Driving Automation.

• Level 0 (No Driving Automation): The vehicles are manually controlled. Some features are designed to “pop up” automatically whenever problems occur.
• Level 1 (Driver Assistance): The vehicles feature single automated systems for driver assistance, such as steering or accelerating (cruise control). 
• Level 2: (Partial Driving Automation): The vehicles support ADAS (steering and accelerating). Here the automation falls short of self-driving because a human sits in the driver’s seat and can take control of the car at any time. 
• Level 3 (Conditional Driving Automation): The vehicles have “environmental detection” capabilities and can make informed decisions for themselves, such as accelerating past a slow-moving vehicle. But they still require human override. The driver must remain alert and ready to take control if the system is unable to execute the task. Tesla Autopilot is qualified as Level 3.
• Level 4 (High Driving Automation): The vehicles can operate in self-driving mode within a limited area.
• Level 5 (Full Driving Automation): The vehicles do not require human attention. There’s no steering wheel or acceleration/braking pedal. We are far from Level 5.

With Tesla Autopilot qualified as Level 3, we are only halfway through the journey to the full driving automation.

However, we personally think that the matter of these Level 3 vehicles is the training data for the AI system. The datasets that have been poured into this are very limited, possibly can be compared to just a drop in the ocean.

 

To train the AI system is no easy task, as the datasets require not only accuracy but also high quality, not to mention the enormous amount of them.

The speed in which Tesla or any other autonomous vehicle company is going for is quite high in order to be ahead of the competition. Instead of doing it themselves, these companies often seek help at some outsourcing vendor for better management and execution of data processing. These vendors can help with both data collecting and data annotating.

Want to join the autonomous market without worrying about data annotation? Get consults from LQA to come up with the best-fitted data annotation tool for your business. Contact us now for full support from experts.

• Website: https://www.lotus-qa.com/
• Tel: (+84) 24-6660-7474
• Fanpage: https://www.facebook.com/LotusQualityAssurance

 

The ever-growing development pace of information technology draws a tremendous need for better speed and flawless execution. So, Automation Testing vs. Manual Testing, which one to go with?

 

As a reflection of this, manual testing is still a vital part of the testing process, non-excludable from the field for some of its specific characteristics. 

Both automation testing and manual testing pose great chances of cost-efficiency and security for your firms. In this article, the three underlying questions of what approach should be applied to your firm for the best outcome will be answered:

• What are the parameters for the comparison between the two?
• What are the pros and cons of automation testing and manual testing?
• Which kind of testing is for which?

 

What is automation testing?

Automation testing is a testing technique utilizing tools and test scripts to automate testing efforts. In other words, specified and customized tools are implemented in the testing process instead of solely manual forces.

Up until now, automated testing is considered a more innovative technique to boost the effectiveness, test coverage, and test execution speed in software testing. With this new “approach”, the testing process is expected to yield more test cases under a shorter amount of time and expand test coverage.

While it does not entirely exclude manual touch within the process, automation testing is a favorable solution for its cost-efficiency and limited human intervention. To put it in other words, automation testing requires manual efforts to make automation testing possible.

 

What is manual testing?

Manual testing, as in its literal meaning, is the technique in which a tester/a QA executes the whole testing process manually, from writing test cases to implementing them.

Every step of a testing process including test design, test report or even UI testing is carried out by a group of personnel, either in-house or outsourced. 

In manual testing, QA analysts carry out tests one-by-one in an individual manner to find bugs, glitches and key feature issues prior to the software application’s launch. As part of this process, test cases and summary error reports are developed without any automation tools.

*Check out:

Why Manual to Automation Testing

6 steps to transition from Manual to Automation testing

 

Magnifying glass for differences between Automation Testing and Manual Testing

Simple as their names are, automation testing and manual testing seem easy to define and identify. However, when looking into the details of many aspects such as test efficiency, test coverage or the types of testing to be applied, it requires a meticulous and strategic understanding of the two.

The differences between automation testing and manual testing can be classified into the following categories:

• Cost
• Human Intervention
• Types of Testing
• Test execution
• Test efficiency
• Test coverage

 

1. Testing cost

For every company, when it comes to testing costs, it requires ubiquitous analysis to weigh in the cost and the benefit to choose a technique for testing.

With the evaluation of potential costs and revenue generated from the project itself, the analysis will determine whether the project needs automation testing or manual testing. As listed in this table, the initial investment, subject of investment and cost-efficiency will be addressed.

Parameters	Automation Testing	Manual Testing
Initial Investment	Automated Testing requires a much larger initial investment to really hit it off. In change for that is the higher ROI yielding in the long run. The cost of automation testing is to cover Automation Testers and open-source automation tools, which can be quite costly.	The initial investment in Manual Testing lies in the cost for human resources and team setup. This may seemingly be economic at first with the cost of just 1/10 of that with automation testing, but in the long-term, the cost can pile up to huge expenses.
Subject of Investment	Investment is resourced for specified and customized tools, as well as automation QA engineers, who expect a much higher salary range when compared to those of manual testing.	Investment is poured into Human Resources. This can be either in-house recruitment or outsourcing, depending on your firm’s request and strategy.
Test volume for cost-efficiency	High-volume regression	Low-volume regression

 

2. Human Resources Involvement

The whole picture of manual testing and automated testing does not simply indulge in the forces that execute the testing, whether it is a human being or a computer. However, there are some universal differences concerning human resources involvement.

Parameters	Automation Testing	Manual Testing
User Interface observation	Automation Testing is basically executed by scripts and codes. Therefore, it cannot score on users’ interaction and opinions upon the software. Matters such as user-friendliness and positive customer experience are out of reach in this case.	The user interface and user experience are put into consideration. This process usually involves a whole team.
Staff’s programming skill requirement	Automation testing entails presets of Most In-Demand programming skills	Manual testing does not necessitate high-profile programming skills or even none.
Salary range	As estimated by Salary.com, the average Automation Test Engineer salary in the United States is approximately 4% higher than that of a regular Software Tester.	The salary range for manual testing is often lower because automated testing requires fluency in different coding languages, which manual testers are incapable of.
Talent availability	It is quite hard for talent acquisition with automation testing engineers.	It is easier for talent acquisitions as the training and coaching for manual testers are easier.

 

3. Testing types

While software testing breaks down into smaller aspects such as performance testing or system testing, Automation Testing or Manual Testing are too general and broad an approach. For each type of testing, we have different approaches, either through an automated one or a manual one. In this article, the following types of testing will be disclosed:

• Performance Testing (Load Test, Stress Test, Spike Test)
• Batch Testing
• Exploratory Testing
• UI Testing
• Adhoc Testing
• Regression Testing 
• Build Verification Testing

Parameters	Automation Testing	Manual Testing
Performance Testing	Performance Testing, including Load Test, Stress Test, Spike Test, is to be tested with Automation Testing.	Manual Testing is not feasible with Performance Testing because of restricted human resources and lack of necessary skills.
Batch Testing	Batch Testing allows multiple test scripts on a nightly basis to be executed.	Batch Testing is not feasible with manual testing.
Exploratory Testing	As exploratory testing takes too much effort to execute, automation testing is impossible	Exploratory testing is for the exploration of the functionalities of the software under the circumstance that no knowledge of the software is required, so it can be done with manual testing
UI Testing	Automated Testing does not involve human interactions, so user interface testing is not feasible.	Human intervention is involved in the manual testing process, so it is proficient to test the user interface with manual testing.
Adhoc Testing	Adhoc testing is performed randomly, so it is definitely not for automation testing.	The core of Adhoc Testing is the testing execution without the instruction of any documents or test design techniques.
Regression Testing	Regression testing means repeated testing of an already tested program. When codes are changed, only automation testing can execute the test in such a short amount of time	Regression testing takes too much effort and too much time to test a changed code or features, so manual test is not the answer for regression testing.
Build Verification Testing	Due to the automation feature, Build Verification Testing is feasible.	It was difficult and time-consuming to execute the Build Verification Testing.

 

4. Test execution

When it comes to testing execution, the expected results are correlated with the actual ones. The answer for “How are automated testing and manual testing carried out?” is also varied, based on the scenario of actual engagement, frameworks, approach, etc.

Parameters	Automation Testing	Manual Testing
Training Value	Automation Testing results are stored in the form of automated unit test cases. It is easy to access and quite straightforward for a newbie developer to understand the codebase.	Manual Testing is limited to training values with no actual documentation of unit test cases.
Engagement	Besides the initial phase with manual testing, automation testing works mostly with tools, hence the accuracy and the interest in testing are secured.	Manual Testing is prone to error, repetitive and tedious, which may cause disinterest for testers.
Approach	Automated Testing is more cost-effective for frequent execution of the same set of test cases.	Manual Testing is more cost-effective for test cases with 1 to 2 test executions
Frameworks	Commercial frameworks, paid tools and open-source tools are often implemented for better outcomes of Automation Testing.	Manual Testing uses checklists, stringent processes or dashboards for test case drafting.
Test Design	Test-Driven Development Design is enforced.	Manual Unit Tests do not involve coding processes.
UI Change	Even the slightest change in the user interface requires modification in Automated Test Scripts	Testers do not encounter any pause as the UI changes.
Access to Test Report	Test execution results are visible to anyone who can log into the automation testing system.	Test execution results are stored in Excel or Word files. Access to these files is restricted and not always available.
Deadlines	Lower risk of missing a deadline.	Higher risk of missing a deadline

 

Also read: Essential QA Metrics to Navigate Software Success

5. Test Efficiency

Test Efficiency is one of the vital factors for a key person to decide whether their firm needs automated testing or manual testing. The fast-paced development of information technology, in general, has yielded more demands in the field of testing, hence skyrocketing the necessity of automation testing implementation.

Regarding test efficiency, automation testing seems to be a more viable and practical approach for a firm with fast execution and sustainability.

Parameters	Automation Testing	Manual Testing
Time and Speed	Automation Testing can execute more test cases in a shorter amount of time	Manual Testing is more time-consuming. It also takes much effort to finish a set of test cases.
Sustainability	Usually, test scripts are written in languages such as JavaScript, Python, or C#. These codes are reusable and quite sustainable for later test script development. Any change can be easily altered with decent skills of coding.	Manual testing does not generate any kind of synchronized documentation for further utility. On the other hand, the skillsets for coding are not necessary.

 

6. Test Coverage

Error detection with Automation Testing is covered more thoroughly. Approaches like reviews, inspections, and walkthroughs are done without leaving anything behind. On the side of manual testing, the numbers of device and operating system permutations are limited. 

 

What are the advantages and disadvantages of automation testing and manual testing?

Automation testing and manual testing both pose great opportunities for the testing industry. For each approach, you have to put many aspects into consideration. In general, automation testing and manual testing have their merits and demerits.

 

Automation Testing pros and cons

Advantages of automation testing

• Reduced repetitive tasks, such as regression tests, testing environments setup, similar test data input
• Better control and transparency of testing activities. Statistics and graphs about test process, performance, and error rates are explicitly indicated
• Decreased test cycle time. Software release frequency speeds up
• Better test coverage

Disadvantages of automation testing

• Extended amount of time for training about automation testing (tools guidance and process)
• The perspective of a real user being separated from the testing process
• Requirement for automation testing tools that can be purchased from third vendors or acquired for free. Each of them has its own benefits and drawbacks
• Poor coverage of the test scope
• Costly test maintenance due to the problem of debugging the test script

 

Manual Testing pros and cons

Advantages of manual testing

• Capability to deal with more complex test cases
• Lower cost   
• Better execution for Ad-hoc testing or exploratory testing
• The visual aspect of the software, such as GUIs (Graphical User Interface) to be covered

Disadvantages of manual testing

• Prone to mistakes
• Unsustainability
• Numerous test cases for a longer time of test execution
• No chance of load testing and performance testing execution

Should you choose automation testing or manual testing?

For each approach of automation testing or manual testing, the question of what to choose for your firm cannot be answered without considering the parametric, the pros and cons of the two.

If your company is a multinational corporation with a vision for large-scale digital transformation, having huge revenue and funds for testing, automation testing is the answer for you. 

Automation testing is sustainable in the long run, enabling your corporation to achieve a higher yield of ROI. It also secures your firm with better test coverage and test efficiency. Automation testing will be the best solution for regression testing and performance testing.

 

If your company seeks a cheaper solution with test case execution under a smaller scope, you should aim at manual testing for a smaller testing cost. User Interface, user experience, exploratory testing, Adhoc testing have to be done with manual testing.

All in all, although automation testing benefits many aspects of the quality assurance process, manual testing is of paramount importance. Please be noted that under the circumstance of frequent changes in test cases, manual testing is compulsory and inseparable from automation testing. The accumulation of the two will generate the most cost-effective approach for your firm.

For the best practices of testing, you should see the automation approach as a chance to perform new ways of working in DevOps, Mobile, and IoT.

 

Want to dig deeper into automation testing vs. manual testing and decide the one for your business? Contact LQA now for a FREE consultation with our specialists and experts.

• Website: https://www.lotus-qa.com/
• Tel: (+84) 24-6660-7474
• Fanpage: https://www.facebook.com/LotusQualityAssurance

 

Data is the foundation of all the AI projects and there are different ways to prepare datasets, including collecting through the internet or consulting an agency. So, what is the best way to get raw data for the AI Data Training process?

One suggested way to collect the train and test data is to visit various open labeled resources like Google’s Open Images and mldata.org or many other websites providing datasets for training in ML projects. These platforms supply you with an endless multitude of data (mostly in the form of images) to start your training process. 

Depending on what kind of datasets you’re looking for, you can divide it into these categories of:

• Open Dataset Aggregators
• Public government Datasets for machine learning
• Machine Learning Datasets for finance & economics
• Image datasets for computer vision

For a high-quality machine learning / artificial intelligence project, datasets for training is the top priority that defines the outcome of the project. For the qualified and suitable datasets, you can consider the following filters to find the most suitable ones.

 

Open Dataset Aggregators

The most common thing that you might be looking for when working on machine learning / artificial intelligence is a source of free datasets. Open dataset finders that you can use to browse through a wide variety of niche-specific datasets for your data science projects. You can find it in:

• 1. Kaggle: A data science community with tools and resources which include externally contributed machine learning datasets of all kinds. From health, through sports, food, travel, education, and more, Kaggle is one of the best places to look for quality training data.
• 2. Google Dataset Search: A search engine from Google that helps researchers locate freely available online data. It works similarly to Google Scholar, and it contains over 25 million datasets. You can find here economic and financial data, as well as datasets uploaded by organizations like WHO, Statista, or Harvard.
• 3. OpenML: An online machine learning platform for sharing and organizing data with more than 21.000 datasets. It’s regularly updated and it automatically versions and analyses each dataset and annotates it with rich meta-data to streamline analysis.

 

Public government Datasets

For machine learning projects concerning social matters, public government datasets are very important. You can find useful datasets in these following sources:

• 4. EU Open Data Portal: The point of access to public data published by the EU institutions, agencies, and other entities. It contains data related to economics, agriculture, education, employment, climate, finance, science, etc.
• 5. World Bank: The open data from the World Bank that you can access without registration. It contains data concerning population demographics, macroeconomic data, and key indicators for development. A great source of data to perform data analysis at a large scale.

 

Machine Learning Datasets for finance & economics

The use of machine learning / artificial intelligence for finance & economics has long been very promising with the vast implementation in algorithmic trading, stock market predictions, portfolio management, and fraud detection. The quantity for this is very big thanks to the datasets built over many years. You can find the easily accessible datasets for finance & economics here:

• 6. Global Financial Development (GFD): An extensive dataset of financial system characteristics for 214 economies around the world. It contains annual data which has been collected since 1960.
• 7. IMF Data: International Monetary Fund publishes data related to the IMF lending, exchange rates, and other economic and financial indicators.

 

Image datasets for computer vision

Medical imaging, automatic cars/self-driving cars are becoming more popular these days. With the high-quality datasets of training visual data, the application of these technologies will be better than ever. You can find the sources here:

• 8. Visual Genome: A large and detailed dataset and knowledge base with captioning of over 100.000 images.
• 9. Google’s Open Images: A collection of over 9 million varied images with rich annotations. It contains image-level label annotations, object bounding boxes, object segmentation, and visual relationships across 6000 categories. This large image database is a great source of data for any data science project.
• 10. Youtube-8M: A vast dataset of millions of YouTube video IDs with high-quality machine-generated annotations of more than 3,800 visual entities. This dataset comes with pre-computed audio-visual features from billions of frames and audio segments.

Finding the suitable datasets for machine learning / AI is never easy. Besides the 4 categories mentioned above, the datasets can be Natural Language Processing Datasets, Audio Speech and Music Datasets for Machine Learning Projects, Data Visualization Datasets. You can check out other free source of datasets for machine learning with V7’s 65+ Best Free Datasets for Machine Learning.

However, the downside is that those open sources are not credible enough, so if your team accidentally gathers wrong data, your ML project will be affected badly, which reduces the level of accuracy for end-users. Also, collecting the data from unknown sources will cost you a great deal of time as it requires a lot of physical and manual labor.

So, the optimal strategy to get high-quality data for the task of labelling is to outsource to a professional vendor who has profound experience and knowledge providing data collection service to AI-based projects.

For your information, Lotus Quality Assurance is an expert at both data collection and annotation services. The datasets that Lotus Quality Assurance collects, including but not limited to images from reliable sources on the Internet, videos and sound captured and recorded with specific scenes, are provided with best quality and accuracy. 

If you have any difficulties in data collecting or data annotation for your projects, feel free to reach out to us!

Lotus Quality Assurance (LQA)

Tel: (+84) 24-6660-7474
Email: [email protected]
Website: https://www.lotus-qa.com/

Continuing with the interview, this time, I want to ask Xuan about her personal life because I believe a a busy leader like Xuan are very good at work-life balance.

 

Thank you for sharing about the work you’ve done. May I ask about your personal life? What is your childhood dream?

When I was a little girl, I wanted to become a painter because my father was a painter. And he made a lot of wonderful pictures. When it came to decide which university to apply for, my father asked if I wanted to become an artist or an engineer. I chose to become an engineer and I did not regret the decision. I love to create technology and want to work full time for it while painting can be my hobby, which means I can paint in my free time.

 

What do you think your characters are?

Ummmm…! What a hard question! I think I’m the kind of person who never gives up, very ambitious. People around me also say the same.

 

 

Who do you respect the most and why?

This is another hard question. I respect everyone because they are different from me and I can learn a lot from these differences. But the person I respect the most is my mother. My mother is the leading example of a person who “never gives up”. My mother brought me up in a challenging situation but she succeeded in raising a great family.

 

What do you do on weekends?

I do two types of activities. To relax, I go out with my friends for a coffee or spend time with my children, or read books, go shopping, so on! I do many things that would make me happy and gain more energy for the new week. Apart from entertainment, I also do some work-related stuff such as reviewing and making plan for the new week. 

 

 

What do you like about Japan?

I like everything about Japan. The people, the food and the surroundings. The first time I’ve been to Japan, I got lost and an old man took me from the airport to my dorm. It was a long distance but he still offered to help me. I felt very lucky at that time. Japanese foods are also very delicious, and the environment is also very clean and clear.

 

Thank you for sharing your thought. Last but not least, I would like to ask about your typical day. As the CEO of LQA, I think you have a very busy personal life, I am curious how you can manage.

 

It’s boooring (smiley face). 

4:30: I get up then quickly check my work such as email, schedule of the day.

5:30 – 6:30: Go to the gym or studying Japanese.

6:30 – 7:30: I make breakfast and enjoy it with my family.

7:30 – 8:00: I take my daughter to school and go to office. 

8:00 – 18:30: Work. 

18:30 – 21:30: I make dinner, play with my children if I don’t need to go out for dinner with clients.

21:30 – 23:00: I work a little bit if have a conference calls or reading book.

23:00: I do some personal stuffs then go to sleep.

You’re such an early bird. What a hectic life! That’s not boooring at all (smile). I really admire you. Thank you very much for finding time in your busy schedule to have a talk with me. I wish you best of luck.

 

From this interview, I learn more about LQA and why LQA was able to grow that fast. I also understand more about Xuan a very passionate and thoughtful person. With Xuan san leading the company, LQA is on the road to success.

If you have not read the Part 1 of this interview, please check it out here. 

 

Watch our introduction video: LQA Introduction

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Lotus Quality Assurance (LQA)

Tel: (+84) 24-6660-7474
Email: [email protected]
Website: https://www.lotus-qa.com/

 

The New Year 2020 comes with a lot of plans and opportunities for LQA. Today, let’s have an interview with Mrs Xuan Phung – the ambitious captain of the ship LQA, to know more about LQA’s goals for this year as well as her life as a businesswoman. 

Happy New Year Mrs Xuan. Thank you for taking the time to talk to me. Firstly, can you share with me about your ultimate goal when you started the company?

We aim to make LQA a global Quality Assurance (QA) company. We want to provide talented QA engineers to companies worldwide. We also want to support clients in making a high quality software products so that the end-users can use it without any errors. Last but not least, I want to make LQA a second home for my teammates where they can continuously grow up professionally and have a happy life.

What were your difficulties when you started your company?

The first difficulty I met was finding the first client. In the beginning, there was only me, no staff.  I faced a lot of obstacles, but I became more familiar with tough situations. I think solving problems and dealing with difficulties are my actual job. At the moment, I don’t think of those challenges as difficulties but as part of my responsibilities to grow the company.

Could you share with me the strength and weakness of this company?

Our strengths are that we specialize in testing, and we spend time and effort in making our services better. Since LQA is becoming more global, the company can cooperate with testing companies in different countries to understand the specific quality standard in these countries. Our team are talented and fast learners with strong determination. Our engineers have international testing certifications (ISTQB). Furthermore, our staff can communicate in many languages such as English, Japanese and Korean. LQA’s weakness is that LQA is a young company, so there are many things to learn as we go. But we always try to learn from each other.

What do you think is the best asset of this company?

I think human capital, my teammates are LQA’s best asset because great staff make quality services and satisfy the clients.

Why do you choose Japan to expand the business this year?

Made in Japan becomes a famous brand representing high quality. We believe that  as LQA offer high quality products, we can also provide our services to Japanese customers. Moreover, I think Japan is a potential market for ITO (Information Technology Outsourcing) because the country lack of human resources, especially IT engineers.

The rest of the interview about Xuan will be published soon. Stay tuned!

Watch our introduction video: LQA Introduction

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Lotus Quality Assurance (LQA)

Tel: (+84) 24-6660-7474
Email: [email protected]
Website: https://www.lotus-qa.com/

“We enjoy working with LQA because of the high quality of their work and their flexibility in accommodating any new task. In the past year, we had a variety of different projects, from simple bounding box annotations to complex pixel-wise segmentation, and every time the team was able to perform the task according to the specification and within the agreed time frame. We are very impressed with the amount of effort the team put into understanding of precise requirements and making sure there are no grey areas in the task before starting the work. The work processes seem very smooth and well organised, making the interactions easy and predictable. So far LQA have been one of our best experiences when working with external annotation teams.” – Daedalean

“Daedalean (www.daedalean.ai) was founded in 2016 with an aim to specify, build, test and certify a fully autonomous sensor and autopilot system that can reliably and completely replace the human pilot. Currently the company is working with EASA on an Innovation Partnership Contract to develop concepts of design assurance for neural networks.”

If you have any difficulties in data collecting or data annotation for your projects, feel free to reach out to us!

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Lotus Quality Assurance (LQA)

Tel: (+84) 24-6660-7474
Email: [email protected]
Website: https://www.lotus-qa.com/

Data Annotation is the process of labelling the training data sets, which can be images, videos or audios. Needless to say, AI Annotation is of paramount importance to Machine Learning (ML), as ML algorithms need (quality) annotated data to process. 

In our AI training projects, we use different types of annotation. Choosing what type(s) to use mainly depends on what kind of data and annotation tools you are working on.

Bounding Box: As you can guess, the target object will be framed by a rectangular box. The data labelled by using bounding boxes are used in various industries, and most used in automotive vehicle, security and e-Commerce industries. 

Polygon: When it comes to irregular shapes like human bodies, logos or street signs, to have more precise outcome, Polygons should be your choice. The boundaries drawn around the objects can give an exact idea about the shape and size, which can help the machine make better predictions.

Polyline: Polylines usually serve as a solution to reduce the weakness of bounding boxes, which usually contain unnecessary space. It is mainly used to annotate lanes on road images.

3D Cuboids: The 3D Cuboids are utilized to measure the volume of objects which can be vehicles, buildings or furniture. 

Segmentation: Segmentation is similar to polygons but more complicated. While polygons just choose some objects of interest, with segmentation, layers of alike objects are labeled until every pixel of the picture is done, which leads to better results of detection.

Landmark: Landmark annotation comes in handy for facial and emotional recognition, human pose estimation and body detection. The applications using data labeled by landmark can indicate the density of the target object within a specific scene. 

If you have any difficulties in data collecting or data annotation for your projects, feel free to reach out to us!

On 19th November, LQA was honored to join “Kanagawa business seminar” – the significant networking event with the participation of Kanagawa government officials, Kanagawa and Vietnamese businesses.

 

Here, LQA CEO Xuan Phung had a conversation with Mr. Yuji Kuroiwa (黒岩 祐治), the Governor of Kanagawa Prefecture, to share with him about LQA’s plan to set up a Japanese subsidiary in Kanagawa. Kanagawa is an ideal place for the establishment, as it offers a range of advantages. In geographical terms, Kanagawa’s capital city – Yokohama, which lies on Tokyo Bay, in the Kantō region of the main island of Honshu, is a major commercial hub of the Greater Tokyo Area. The prefecture’s government also gives special preference to foreign businesses. 

 

 

Mr. Yuji Kuroiwa was delighted with this plan of LQA, and he believed that this would be a great step forward for the company. The government will be willing to help LQA so that the company can develop, achieve much success in Japan.