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Automated Attendance system uses face biostatics accompanied by the techniques of image processing and machine learning algorithms to recognize students. Face recognition technology complementary to Image Processing is gradually evolving to a universal biometric solution since it does not require any virtual effort from the user as compared to other biometric options. The main objective is to develop a real-time attendance monitoring system that overcomes the shortcomings of existing methods. The approaches vary in terms of input methods used, type of data processing employed and the…mehr

Produktbeschreibung
Automated Attendance system uses face biostatics accompanied by the techniques of image processing and machine learning algorithms to recognize students. Face recognition technology complementary to Image Processing is gradually evolving to a universal biometric solution since it does not require any virtual effort from the user as compared to other biometric options. The main objective is to develop a real-time attendance monitoring system that overcomes the shortcomings of existing methods. The approaches vary in terms of input methods used, type of data processing employed and the controllers used in the implementation of the systems. The Proposed System is provided with snaps on which face detection and recognition technique is applied. After faces are detected, they are recognized by matching them with existing database, system updates the attendance for all recognized members with their respective id. An excel sheet is generated for the attendance record.
Autorenporträt
Er. Mani Bhushan Jauhari, Er. Metali Thareja são os graduados da Shri Ramswaroop Memorial College of Engineering and Management Lucknow. Concluíram o seu Bacharelato em Tecnologia Informática e Engenharia.O Dr. Atul Kumar trabalha como Professor Associado e Chefe de Departamento no Departamento de Ciência e Engenharia Informática.