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This is a Smart Attendance System designed using a pre-trained model called Haar-Cascade Classifier, OpenCV and other various Dependencies to mark the attendance in a smarter way and saves the lecture time.
IPTS (Intelligent Participant Tracking System) uses facial recognition to accurately monitor and track individuals in real-time for enhanced security and efficient participant management.
Designed and implemented a QR-Based Attendance project that enables efficient attendance tracking for Teaching organizations. Generates attendance reports. Developed using Python and its libraries.
Developing a Smart Attendance Marking System (SAMS) that can be used by colleges,schools and various organizations to facilitate the easy maintenance of the daily attendance records of students or employees.
Attendance System using face recognition. Fully automated, UI operated. The model was trained using Keras Sequential layers and Softmax function at the output layer. The data is maintained in MongoDB and CSV at the backend. UI is created using Tkinter