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https://github.com/rajsoni06/face_recognition_attendance-_system
https://github.com/rajsoni06/face_recognition_attendance-_system
Last synced: 3 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/rajsoni06/face_recognition_attendance-_system
- Owner: rajsoni06
- Created: 2024-08-09T18:21:48.000Z (3 months ago)
- Default Branch: master
- Last Pushed: 2024-08-09T18:44:03.000Z (3 months ago)
- Last Synced: 2024-08-09T20:10:43.731Z (3 months ago)
- Language: HTML
- Size: 16.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
Face Recognition Attendance System
Overview
This project involves the development of an advanced Face Recognition Attendance System using Neural Networks and Convolutional Neural Networks (CNNs). The system is designed to accurately identify students, extract facial features, and automate the attendance recording process, demonstrating the practical application of Machine Learning (ML) techniques in real-world scenarios.
Features
Sophisticated Facial Recognition: Employs state-of-the-art Neural Networks and CNNs for accurate student identification.
Automated Attendance Recording: Efficiently logs attendance data based on facial recognition, reducing manual effort.
Feature Extraction: Implements advanced ML algorithms to extract and process facial features.
User-Friendly Interface: Developed using the MERN stack for an intuitive and responsive user interface.
Scalable and Flexible: Designed to be easily scalable and adaptable to various environments and use cases.
Tools & Technologies Used
Python: For backend development and ML model implementation.
Django: Framework used for developing the web application backend.
Neural Networks & CNNs: Core technologies behind the facial recognition model.
MERN Stack:
MongoDB: Database management.
Express.js: Backend framework.
React.js: Frontend library for building the user interface.
Node.js: Server-side runtime environment.