Attendance System using Open Face Model and Support Vector Machine
Provide facenet training model download, regularly updated
Automated registrations for meetups and events. Makes way for a constant and smooth flow for crowded events.
Detecting the human subject other than the family members through the CCTV footage and alerting the house owner through the mail.
Created a Distributed platform that provides face recognition based automatic attendance at a scheduled time. The platform also keeps track of the details like for how many hours was a person present . Hence provides a solution for institutes for marking attendance of the students automatically at the scheduled time and for the organizations to …
WYNA is a tiny bot asking your name and remembers your face and your name on next encounter
Detection and recognition of a person in real time live video sequences.
This project uses Convolutional Neural Network to detect a person's face Using HAR feature. Then the person can be also recognized even if it was trained on only 1 image.
This project can detect a person and also recognize after trained on very limited data using Convolutional Nueral Network.
Smart attendance Desktop app built using facenet pr-trained model
This is a self mini project that I undertook for my learning process. I have taken an episode from my favourite TV series called The Office (US) S06E01. Using this episode I have extracted images & using those images I have classified 17 characters using CV2 and Facenet Model.
Python application for face detection and recognition using various algorithms.
Face Recognition using FaceNet
A web app that authorizes a user with their face.
A Face Recognition using tensorflow. This code was copied from https://github.com/habrman/FaceRecognition/ and modified into an api to recognize faces of some celebrities
Face recognition pipeline based on Facenet and MTCNN including image preprocessing (denoise, dehazing,...) with image augmentation techniques
This is a modern Face Authentication System which includes state-of-art algorithms to detect face and generate face embedding. This system contains endpoints which can be integrated to any device depending on the requirements.
Face Recognition and Classification Using FaceNet and MTCNN
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