Recent advancements in artificial intelligence and machine learning allowed for the adoption of facial recognition and biometric technology in numerous industries, which created new opportunities and use cases for facial recognition. When the technology was first introduced, there were some concerns about its reliability, especially in organizations dealing with finance or security. However, today, according to the National Institute of Standards and Technology (NIST) the best facial recognition technology had an error rate of only .08 percent as of April 2020. Different technologies are used to help with facial recognition: some of them can be free and can be quickly deployed without machine learning expertise, like CompreFace. Others cost tens of thousands of dollars per year. Check out how much integration with facial recognition software costs.
More companies within different industries are starting to integrate facial recognition technology to address attendance management, set up effective marketing campaigns or to create better customer experiences, providing better personalization to the clients.
Read the full article on JAXenter by Serhii Pospielov, Exadel AI Practice Lead to learn about use cases for facial recognition and industries where this AI technology is broadly applied.