Abstract:
With the increasing demand for efficient and secure attendance tracking systems, this project introduces an Automated Face Recognition Attendance System implemented in Python. The proposed system leverages state-of-the-art facial recognition techniques to accurately identify and authenticate individuals, eliminating the need for traditional attendance methods such as manual entry or card swiping.
The system utilizes computer vision libraries, particularly OpenCV, and deep learning frameworks like TensorFlow or PyTorch for robust face detection and recognition. A pre-trained deep neural network model is employed to extract distinctive facial features, enabling reliable and real-time identification of individuals in various environmental conditions.