MTCNN and FACENET-Based Face Detection and Recognition Model for Attendance Monitoring

Author:

Roy Manas KumarORCID,Dwibedi PreronaORCID,Singh AnniORCID,Chakraborty Ram PrasadORCID,Mondal Md Keramot HossainORCID

Publisher

Springer Nature Singapore

Reference10 articles.

1. Chumming, W., Ying, Z.: MTCNN and FACENET based access based control system for face detection and recognition. Autom. Control Comput. Sci. 55(1), 102–112 (2021)

2. Jayaswal, R., Dixit, M.: Comparative analysis of human face recognition by traditional methods and deep learning in real-time environment. In: IEEE 9th International Conference on Communication Systems and Network Technologies (CSNT), pp. 66–71. IEEE (2020)

3. Reddy, N., Sumanth, M., Babu, S.: A Counterpart approach to attendance and feedback system using machine learning techniques. J. Emerg. Technolog. Innov. Res. (JETIR) 5(12) (2018)

4. Chandramouli, B., Kumar, S.A., Lakshmi, C.V., Harish, G.B., Khan, P.A.: Face recognition based attendance management using Jetson Nano. Int. Res. J. Mod. Eng. Technol. Sci. 3(8) (2021)

5. Sutar, H., Chaudhari, S., Bhopi, P., Sonavale, D.: Automated attendance system using deep learning. Int. Res. J. Mod. Eng. Technol. Sci. 4(04) (2022)

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