Deep Learning Based Face Recognized Attendance Management System using Convolutional Neural Network
- Title
- Deep Learning Based Face Recognized Attendance Management System using Convolutional Neural Network
- Creator
- Joseph A.; Nair A.; Koshy A.B.; Nallaballi M.; Jayapandian N.
- Description
- In today's digital age, manual attendance tracking is plagued by inefficiency and the potential for inaccuracies, often leading to proxy attendance. The main aim of this research work is to manage and monitor the student's attendance by using face recognition technology. This proposed model is mainly categorized four major modules. First module is database creation. Second module is face detection. Then third module is face recognition and final module is automatic attendance updating process. Student images are compiled to create a comprehensive database, ensuring inclusivity across the class roster. The system utilizes the face recognition library, which relies on deep learning based algorithms for face detection and recognition during testing. This face recognition part Convolutional Neural Network algorithm is used. The system matches detected faces with the known database and marks attendance, ensuring a streamlined and accurate attendance tracking process. This innovative approach has the potential to revolutionize attendance management in educational settings, offering a contactless and efficient solution while mitigating proxy attendance concerns. The proposed model is to compare the accuracy level of face recognition. 2023 IEEE.
- Source
- 3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023
- Date
- 2023-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Convolutional Neural Network; Database Management; Deep Learning; Face Recognition; Generative Adversarial Networks
- Coverage
- Joseph A., (Deemed to Be University), Department of Cse Christ, India; Nair A., (Deemed to Be University), Department of Cse Christ, India; Koshy A.B., (Deemed to Be University), Department of Cse Christ, India; Nallaballi M., School of Engineering and Technology Christ (Deemed to Be University), India; Jayapandian N., School of Engineering and Technology Christ (Deemed to Be University), India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835034327-4
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Joseph A.; Nair A.; Koshy A.B.; Nallaballi M.; Jayapandian N., “Deep Learning Based Face Recognized Attendance Management System using Convolutional Neural Network,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/19706.