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{"references": ["Ajay A. Gidd, &Ajinkya S. Shewale. (2020). One Look at Deep Learning Algorithms. Recent Innovations in Wireless Network Security, 2(1), 1\u2013 5.", "Patil, A., & Shukla, M. (2014). Implementation of classroom attendance system based on face recognition in class. International Journal of Advances in Engineering & Technology, 7(3), 974.", "Balcoh, N. K., Yousaf, M. H., Ahmad, W., & Baig, M. I. (2012). Algorithm for efficient attendance management: Face recognition based approach. International Journal of Computer Science Issues (IJCSI), 9(4), 146.", "Viola, P., & Jones, M. J. (2004). Robust real-time face detection. International journal of computer vision, 57(2), 137- 154.", "Zhang, L., Tjondronegoro, D., & Chandran, V. (2012, July). Discovering the best feature extraction and selection algorithms for spontaneous facial expression recognition. In 2012 IEEE International Conference on Multimedia and Expo (pp. 1027-1032). IEEE.", "Chatrath, J., Gupta, P., Ahuja, P., Goel, A., & Arora, S. M. (2014, February). Real time human face detection and tracking. In 2014 international conference on signal processing and integrated networks (SPIN) (pp. 705- 710). IEEE.", "Rahim, M. A., Azam, M. S., Hossain, N., & Islam, M. R. (2013). Face recognition using local binary patterns (LBP). Global Journal of Computer Science and Technology.", "He, D. C., & Wang, L. (1990). Texture unit, texture spectrum, and texture analysis. IEEE transactions on Geoscience and Remote Sensing, 28(4), 509-512.", "Vishwakarma, S., & Pathak, K. (2014). Face recognition using LBP-LCP coefficient vectors with SVM classifier. Int. J. Electron. Commun. Comput. Eng, 5(2), 2278-4209.", "Patil, A. M., Kolhe, S. R., & Patil, P. M. (2009, December). Face recognition by PCA technique. In 2009 Second International Conference on Emerging Trends in Engineering & Technology (pp. 192-195). IEEE.", "Tiwari, P. A., Jha K., Uchil K. P., Naveen H (2015). Haar Features Based Face Detection and Recognition for Advanced Classroom and Corporate Attendance. IJIRCCE, 3(5)."]}
Face recognition has a lot of popularity in the various purposes like security purpose, biometric control, gender classification, for students or employee’s attendance. By calling a roll number by teachers this take so much time, this method is not applicable for the class whose number of students is high. This system takes small time to make the attendance of the students, which will use for the students. There are four techniques of our attendance system, first we create a testing database, then we take the testing photo of students in the classroom, then we match the faces with the testing database.
Face recognition, raspberry pi, OpenCV, face detection
Face recognition, raspberry pi, OpenCV, face detection
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