Face recognition, as one of the most successful applications of image analysis, has recently gained significant attention, especially during the past several years. Our idea proposes an automatic face recognition attendance system for students using raspberry pi and mini cameras based on deep learning and narrowband Internet of things. The system automatically detects and identifies faces and mark present/absent of students with the help of face detection and it points out the technical challenges of building a face recognition system. The system will automatically update the student’s presence in the class to the student’s database and update all the data to the cloud as well as sends It will message to the guardians of absentees and also to the Head of the department. Face recognition processing, including major components such as face detection, tracking, alignment, and feature extraction, and it points out the technical challenges of building a face recognition system. We focus on the importance of the most successful solutions available so far. The final part of the chapter describes chosen face recognition methods and applications and their potential use in areas not related to face recognition.
Python
STUDENT-ATTENDENCE-USING-FACE-RECOGNITION
Face recognition, as one of the most successful applications of image analysis, has recently gained significant attention, especially during the past several years. Our idea proposes an automatic face recognition attendance system for students using raspberry pi and mini cameras based on deep learning and narrowband Internet of things. The system automatically detects and identifies faces and mark present/absent of students with the help of face detection and it points out the technical challenges of building a face recognition system. The system will automatically update the student’s presence in the class to the student’s database and update all the data to the cloud as well as sends It will message to the guardians of absentees and also to the Head of the department. Face recognition processing, including major components such as face detection, tracking, alignment, and feature extraction, and it points out the technical challenges of building a face recognition system. We focus on the importance of the most successful solutions available so far. The final part of the chapter describes chosen face recognition methods and applications and their potential use in areas not related to face recognition.
