Welcome to the Attendance System with Face Recognition repository! This project serves as a Proof of Concept (POC) web application that showcases the application of facial recognition technology for efficient attendance management.
The purpose of this Attendance System Using Face System is to record the presence or attendance of employee through a browser by recognizing the faces captured through a webcam. For this record-keeping, a database was built to store the in-time and out-time of the employee.
Fully functioning face recognition module with less racial bias. -ongoing research project-
We are proposing a solution to overcome the drawbacks of the existing traditional electoral system. In this proposed system, we are assuming a dummy Aadhaar like database for verification and authentication of voters. This solution offers an end-to-end paperless electoral system, ensuring high security in the process and eliminating the risk of …
This project uses State of the Art Facial Recognition model FaceNet to recognise Avengers from the Avenger Dataset.
Biometric attendance system
A website that uses ML-algorithms to detect the facial patterns of a person and detect the identity and facial emotion of the person. The tech-stack includes html, css, js and django
client/server application for easy managing face recognition outputs for a specific image source
Automatic class attendance monitoring application using OpenCV for python and attendance management platform using Flask
My web development portfolio
An image classification application using resnet model
Message Encryptor using facial based entity authentication.
Final project of team HGCG for Advanced Software Engineering (COMS W4156)
Image processing assignments for CS663
Actor face-search chrome-extension that integrate with VisageCloud's face-recognition & search API
Location Based Attendance portal with Face Recognition created using flask, HTML/CSS, JavaScript
Identification of humans using CV2 Haar-like features and classification of dogs using CNN and pretrained CNN(transfer learning).
Hybrid nature-inspired optimization technique, applied on face recognition
Face Detection Using a Javascript library called clmtrackr which will do the heavy work of detecting where the face is on an image, and will also identify facial features such as the nose, mouth, eyes, and more.
Add a description, image, and links to the face-recognition topic page so that developers can more easily learn about it.
To associate your repository with the face-recognition topic, visit your repo's landing page and select "manage topics."