Quality-Aware Face Recognition for Low-Quality and Occluded Images

Face recognition is one of the key artificial intelligence technologies applied to authentication, attendance marking, access control, surveillance, and identification processes. The recognition accuracy can be hampered by the poor image quality of the input photo, for example, if the image was captured under poor conditions or suffers blur, noise, low resolution, pose variation, or occlusion. An AI-powered approach to face recognition is proposed, which allows identifying person using web interface. The process involves detecting, extracting features, recognizing input image to provide the recognition result. The attention-based feature enhancement and quality-aware recognition mechanisms are applied ensure reliable processing of low-resolution facial images. The system under consideration offers accessible and convenient solution to the recognized problem.