NtechLab expands AI-based solutions in Thai urban society

(Center) Ms Liana Meliksetyan, Chief 
Commercial Officer and (2nd from the right) Dmitry Tameev, Head of Business Development & 
Sales (Asia Pacific), NtechLab
(Center) Ms Liana Meliksetyan, Chief Commercial Officer and (2nd from the right) Dmitry Tameev, Head of Business Development & Sales (Asia Pacific), NtechLab

The advantages of security and safety have prompted many government agencies and industries to implement facial recognition technology into their daily operations, typically associated with immigration and the security sector, according to Dmitry Tameev, Head of Business Development & Sales (Asia Pacific) at NtechLab.

 

Facial recognition is everywhere now.    Simple daily uses start from unlocking the smartphones, tagging friends in social media or going through airports and immigration, or opening new accounts online through KYC verification process of account owner’s identity. 

 

Businesses use the technology for a variety of reasons, including verifying and/or identifying individuals to grant them access to online accounts, authorizing payments, tracking and monitoring employee attendance, targeting specific advertisements to shoppers based on gender, age, other attributes, and ethnic groups and much more.

 

Tameev said Asia Pacific market for facial recognition technology is promising and increasing fast.  Especially those markets in Taiwan, Malaysia, Vietnam, Indonesia and Thailand, NtechLab’s AI-based video analytics solutions eg facial recognition and silhouette tracking help businesses and consumers to build safe and smart cities. 

 

NtechLab is also looking business opportunities in Thailand’s digital transformation era and smart cities.  The company has continued supports and share their expertise to help Thais achieving the goal.   Young tech talents, data scientists, professionals in various sectors are recommended to accompany the joint projects.

 

NtechLab’s facial recognition system has nearly absolute precision reaching 99.99% accuracy and 0.1 seconds detection speed.  Since the outbreak of COVID-19, facial recognition software has been upgraded their algorithms with new features, such as recognizing faces with a mask on.   The company is ranked second in the world for face recognition accuracy with medical mask on, according to the U.S. National Institute of Standards and Technology (NIST) under Face Recognition Vendor Test.

 

Key features leading to NtechLab’s success are high-performing algorithms with high accuracy and work with data from real time video streams, large photo and video archives, API that allow to quickly integrate different modules into any third-party devices and services, the software has an integrated anti-spoofing system that works on any camera and distinguishes a live person from an image, and established track records with partners worldwide.

 

With successful implementation in Russia, it shows that over 50,000 crimes solved, more than 5,000 missing people found using video survelliance system, burglaries and car thefts decreased by 85%, solved murdered rate reached 92%, 500,000 shoplifting cases prevented with saving more than an estimated USD10 million.

 

Facial recognition software uses a mix of artificial intelligence (AI) and biometric technology to identify human faces through measuring nodal points, the distances between certain facial features.   Computer vision (CV) is the subbranch of AI that focuses on the problem of teaching computers to see.  CV includes the capabilities in increasing complexity; image capturing and processing, object detection and image segmentation, object recognition, object tracking, gesture and movement recognition, scene understanding.

 

The software analyzes and compares patterns of a person's facial features to provide accurate verification of their identity. It uses biometric algorithms to map, analyze, and confirm the identity of a face on a photo or a video. Although every facial recognition solution (which often rely on proprietary algorithms) operates differently, it involves 3 fundamental steps; detection, analysis, and recognition.

 

 

Facial recognition technology adds convenience and safety to everyday experiences, like using banking services, receiving healthcare, or shopping. It enables a more secure entry to places of business, identify suspicious behaviors, ensure safety in crowded venues, prevent all types of fraud, and make using online services a safer experience.

 

It also helps increasing the quality of customer service, especially in retail and healthcare. For example, speedy self-checkout payment system in stores, knowing who enters a store and tapping into their buying habits, retailers may adjust their offer on the go to better suit the needs of the customer. In healthcare settings, facial recognition can also help craft personalized care plans and service patients way faster.

 

In fact, the global facial recognition market size is forecast to reach $12.67 billion by 2028, up from $5.01 billion in 2021, according to The Insight Partners. This increase is also driven by the growing demand from governments and law enforcement agencies, which use the technology to assist in criminal investigations, conduct surveillance or other security efforts.

 

 

There are potential disadvantages to using facial recognition, including privacy and security issues.

 

The most significant privacy implication of facial recognition technology is the use of the technology to identify individuals without their consent.  It is important for organizations to let users know what biometric data they are collecting and then get their consent.

 

Any biometric, including facial recognition, is not private, which also leads to security concerns.  Biometrics can be copied and that does present security challenges.  With facial recognition, it may be possible to ‘spoof’ a system by using pictures or 3D masks created from imagery taken of a victim.

 

Hence, businesses and tech vendors should prioritize building transparent and explainable solutions, amid public debate about the safety of facial recognition and incomprehensive legislation.