FACE RECOGNITION BASED SMART ATTENDANCE SYSTEM USING MACHINE LEARNING
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Abstract
Face is the crucial part of the human body that uniquely identifies a person. Using the face characteristics as biometric, the face recognition system can be implemented. The most demanding task in any organization is attendance marking. In traditional attendance system, the students are called out by the teachers and their presence or absence is marked accordingly. However, these traditional techniques are time consuming and tedious. In this project, the Open CV based face recognition approach has been proposed. This model integrates a camera that captures an input image, an algorithm for detecting face from an input image, encoding and identifying the face, marking the attendance in a spreadsheet and converting it into PDF file. The training database is created by training the system with the faces of the authorized students. The cropped images are then stored as a database with respective labels. The features are extracted using LBPH algorithm.
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References
Smart Attendance System using Computer Vision and Machine Learning Dipti Kumbhar#1 , Prof. Dr. Y. S.
Angal*2 # Department of Electronics and Telecommunication, BSIOTR, Wagholi, Pune, India 1
diptikumbhar37@gmail.com , 2 yogeshangal@yahoo.co.in
ATTENDANCE SYSTEM USING MULTI-FACE RECOGNITION 1P. Visalakshi, 2Sushant Ashish 1Assistant
Professor 1,2Department of Computer Science and Engineering SRM Institute of Science and Technology, Chennai,
Tamil Nadu, INDIA
Face Recognition Based Student Attendance System with OpenCV CH. VINOD KUMAR1 , DR. K. RAJA
KUMAR2 1 PG Scholar, Dept of CS& SE, Andhra University, Vishakhapatnam, AP, India. 2Assistant Professor,
Dept of CS& SE, Andhra University, Vishakhapatnam, AP, India. [4] Automatic Attendance System Using Face
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Information Science and Engineering, The National Institue of Engineering,
Face Recognition based Attendance Management System using Machine Learning Anushka Waingankar1, Akash
Upadhyay2, Ruchi Shah3, Nevil Pooniwala4, Prashant Kasambe5
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