They have been at work on a facial recognition mission which has attracted great interest; their tool is effective but it also raises some concerns about privacy, if the tool were abused.
Their algorithm can extract facial feature characteristics, which has become a hot topic.
Luke Dormehl, UK-based tech writer at Digital Trends said in June that NTechLab may have stumbled upon one of the best facial recognition systems around.
NTechLab was founded last year by Artem Kuharenko.
They use techniques in artificial neural networks and machine learning to develop software products.
"A face recognition system already developed by our lab, has proved to be among the most accurate ones throughout the world," they stated.
Dormehl talked about their good performance at a competition. "At last year's "MegaFace" facial recognition competition in Washington, it managed to best a number of rivals—including Google's own FaceNet."
(Inverse said NTechLab at that event took fourth place with 73 percent accuracy in the competition, where MegaFace tasked its competitors with identifying faces from photos.)
Facial recognition in the bigger picture was the topic of an article in The Atlantic in June, which made the point that "machines still have limitations when it comes to facial recognition." Scientists are beginning to understand the constraints. "To begin to figure out how computers are struggling, researchers at the University of Washington created a massive database of faces—they call it MegaFace—and tested a variety of facial recognition algorithms as they scaled up in complexity."
Now in October, Nathaniel Mott reports in Inverse, security cameras around Moscow might soon be connected to the NTech Lab facial recognition tool. It would be used for scanning crowds and trying to identify each individual person within them.
Mott wrote that "Moscow has reportedly tapped a young startup called NTechLab to provide the facial recognition software used in this system."
Kelsey Atherton in Popular Science also looked at what they are doing. The article is headlined "Software that identifies any passing facer is ready for market," and the subhead is "Russian police are a likely first customer."
Atherton wrote, "The program uses machine learning: training algorithms to recognize specific faces again and again by feeding images over and over until the algorithms get it right."
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