• Saran M S
• Rounakdeep Singh
• Sukesh S T
• Pavithraa M S
• Soundharya K

The provided Python code presents a sophisticated face recognition attendance system tailored for educational institutions or other organizations. Leveraging the face recognition library, it excels in accurate face detection and recognition within live video streams. Integration with Firebase services enable seamless storage and retrieval of student data and attendance records, promoting flexibility and efficiency. The user interface emphasizes real-time visualization and offers various operation modes for administrators and end-users. Robust error-handling mechanisms ensure reliability, while intelligent prevention of multiple registrations enhances data consistency. The system's cloud-based integration with Firebase and robust error-handling mechanisms ensures reliable and flexible attendance management, showcasing the potential of advanced technologies in modern educational and organizational contexts. Overall, this system represents a comprehensive solution, combining advanced face recognition technologies with cloud-based database management to meet the evolving needs of attendance tracking

Keywords: CNN (Convolutional Neural Network), PNG (Portable Network Graphics), CV2(Computer Vision 2), IDE (Integrated Development Environment), CVZONE (Computer Vision Zone)

"Face Recognition Attendance System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.h23-h30, June-2024, Available :http://www.jetir.org/papers/JETIR2406704.pdf

"Face Recognition Attendance System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pph23-h30, June-2024, Available at : http://www.jetir.org/papers/JETIR2406704.pdf