Paper Title
ML-Based Attendance System

Abstract
This paper presents a Machine Learning-Based Attendance System designed to revolutionize traditional methods of student attendance management. The system combines facial recognition with Optical Character Recognition (OCR) of student ID cards to ensure secure and reliable attendance tracking. The system integrates anti-spoofing mechanisms like blink detection and single-person detection, thus eliminating the possibility of fraudulent entries using photographs or videos. By leveraging Python-based tools including OpenCV, MediaPipe, and Tesseract, this real-time system streamlines the entire attendance process and provides a comprehensive, scalable solution with live analytics through a web dashboard. Keywords - Face Recognition, Optical Character Recognition (OCR), Anti-Spoofing, Machine Learning, Attendance System, Python, Real-Time Verification