Automating Student Attendance Through Face Recognition and Machine Learning Techniques
Year: 2024
Type: article
Abstract: In recent years, facial detection and recognition technologies have become increasingly important in various fields, including smartphones, defence, and secure information centres. Acknowledging their potential, we intend to create a device that uses facial recognition as an effective and innovative substitute for conventional attendance methods, such as paper and fingerprint systems. The primary goal of this project is to establish a unified attendance system that employs facial recognition technology to confirm student identities and simplify the attendance process. This method provides a smooth, secure, and precise solution for contemporary academic settings. The system employs a machine learning algorithm developed for use in Python, allowing it to take pictures of students using the camera on a computer or laptop. Moreover, external cameras can be utilized as long as they are linked to the system. The face recognition capability is implemented through the Haarcascade algorithm, which is incorporated into the software.
Authors: Pratik Patil -, Parth Kulat -, Krishna Jodh -, Shivanjali Khodade -, Manisha Mali -
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4404958480