Face Recognition Smart Attendance System using Convolutional Neural Networks

被引:0
作者
Manimekalai, M. A. P. [1 ]
Daniel, Esther [1 ]
Neebha, T. Mary [1 ]
Muthulakshmi, K. [2 ]
Jess, C. Ryan Paul [1 ]
Raguram, S. [1 ]
机构
[1] Karunya Inst Technol & Sci, Coimbatore, India
[2] Sri Krishna Coll Engn & Technol, Coimbatore, India
来源
PRZEGLAD ELEKTROTECHNICZNY | 2024年 / 100卷 / 05期
关键词
Attendance; CNN (Convolutional Neural Networks); face images; extraction; IoT (Internet of Things);
D O I
10.15199/48.2024.05.46
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
. An automated face attendance system using Convolutional Neural Networks (CNN) is a promising technology for improving attendance management in educational institutions, workplaces, and other organizations. This system uses a deep learning model based on CNN to detect and recognize faces from images captured by a camera. The captured image is pre-processed by applying various techniques such as face detection, extraction, and normalization to extract facial features. The extracted features are then stored in a real-time database and used to train the CNN model to recognize the faces of individuals accurately. The system can efficiently handle various lighting conditions and pose variations to recognize individuals. The proposed method provides a fast and accurate approach to attendance management that can significantly reduce manual efforts and errors.
引用
收藏
页码:244 / 247
页数:4
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