• DR.SANDEEP BHAT
• SHANA SANTHOSH
• ARSHANDH RS
• ABHAY VK

Traditional attendance systems are often prone to inaccuracies, proxy attendance, and time consumption. This project proposes an automated attendance system using face recognition technology that ensures accuracy, security, and efficiency. The system uses computer vision and deep learning techniques to detect and recognize faces in real-time using a live webcam or CCTV feed. The architecture integrates OpenCV for image processing and a convolutional neural network (CNN) model trained on student facial data to automate the marking of attendance. The implementation ensures minimal human intervention while improving reliability and saving time. Results from testing show high accuracy in various lighting and classroom conditions, making the system a viable replacement for manual methods.

Face Recognition, Attendance System, OpenCV, Deep Learning, CNN, Computer Vision

"FACE RECOGNITION USING ATTENDANCE SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.358-364, July-2025, Available :http://www.jetir.org/papers/JETIRGX06065.pdf

"FACE RECOGNITION USING ATTENDANCE SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp358-364, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06065.pdf