Deep_learning specialization course by andrew NG from Coursera
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Updated
Nov 15, 2019 - Jupyter Notebook
Deep_learning specialization course by andrew NG from Coursera
Face recognition using Facenet Model
Face recognition system using FaceNet and OpenCV.
Face Detection using Open CV library on House Full 4 movie trailer.
A face recognition API
Flask based web application to manage attendance using face recognition
using mxnet gluon api build mobilefacenet model to training face data
My graduation thesis project, awarded a 9.5/10, involved creating a student attendance management system for iOS devices that utilizes FaceNet facial recognition model for efficient and secure attendance tracking.
Face detection, and recognition using MTCNN,FACENET, HAAR CASCADES and CAFFE MODELS
This project uses State of the Art Facial Recognition model FaceNet to recognise Avengers from the Avenger Dataset.
Face recognition using Facenet, SVM, MTCNN and PyTorch. Face detection, feature extraction and training for custom datasets.
Real-Time Face Identification using Convolutional Neural Networks
This repository contains program for face recognition using transfer learning.
Coursera - CNN Programming Assignment: In this project, we will build a face recognition system with FaceNet. Face recognition is a method of identifying or verifying the identity of an individual using their face in photos, video, or in real-time
Create your own databse, compile tripletloss with pre-trained FaceNet model, run real-time face recognition on local host
This is a kaggle Challenge. Given a pair of images of 2 faces we have to determine whether they are related or not. Here I have used a Siamese network over VGG-facenet to tackle this problem.
Face recognition using Deep learning methods
Education/Institutional level Project about getting attendance done by face recognition (FaceNet Model) and added functionalities like Getting pdf or excel sheet of Attendance
This repository hosts a cutting-edge facial recognition system designed to enhance customer identification and verification. Leveraging MTCNN for accurate face detection and DeepFace-FaceNet for facial embeddings, the system integrates with Pinecone's vector database to efficiently match and verify repeat customers.
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