Moscow

Neurocore

The system operates with different lighting, camera quality and location of objects. More than 10 thousand &nbsp; images of people of different sex and age were used while creating the module.

It works with various types of computing power: both processors and video cards. As of April 2020, the system operates using API connection.

Neurocore: facial recognition

biometry

computer_vision

artificial_intelligence

Module based on computer vision technologies using video surveillance cameras allows to automate control over an object and optimize the overall process of allowing vehicles to enter a territory with a limited access level. Various neural network architectures were selected and tested during the development process, and the optimal one was developed.

The number of images with objects that were memorized by the system is about 1 million. The system operates with both CPU and GPU. High recognition accuracy is achieved by the algorithm of developing and implementing the solution: over 70% of the training cycles are conducted in a "test environment". The current solution works using the client’s API, integration is possible in more complex conditions.

Vehicle license plate number and class recognition system

transportation

Neurocore: car recognition

Alfa_Bank

fintech

voice_assistants

call_centers

voice_synthesis

Voice Bot

tele_med_ai

AI-based medical research analysis service

medicine

covidtech

Hub Telemed

Locksystems

smart_home

Huse lock

neurocore