Scientists from the National Research University of Technology (MISIS) developed an intelligent system together with experts from the National Research University Higher School of Economics and the Artificial Intelligence Institute (AIRI). It has the ability to automatically select the most effective neural networks for facial recognition services such as Face ID. This significantly speeds up the performance of such services on devices such as smartphones, tablets and smart home devices.
Facial recognition services such as Face ID usually consist of several layers of neural networks, each performing a different function during the image analysis process. The system developed by NUST MISIS is software that can speed up and simplify component selection for Face ID to get the best results. It is important to note that the choice of components depends on the specifications of the specific device on which the system runs. These customized Face ID systems can quickly and accurately recognize faces in 5-10 milliseconds, even on devices with low processing power.
The main benefit of this development is that it can accelerate the adoption of facial recognition systems in organizations where different devices with different processing power are available. For example, if you have a lot of different tablets, this system will help you quickly adapt the facial recognition service to each device, even if their features are different. Manually selecting components for Face ID can be time-consuming and does not always guarantee that the service works correctly on all devices.
The program, created by Russian scientists, is based on open source code and can be downloaded from the GitHub portal. This technology is also described in a scientific article published in the IEEE Access journal.
Source: Ferra
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