A simple implementation of facial recognition using facenets for humans 🧔 🔍
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Updated
Jun 6, 2022 - Python
A simple implementation of facial recognition using facenets for humans 🧔 🔍
Face Recognition using the FaceNet model and MLKit on Android.
Implementation of Facial Recognition System Using Facenet based on One Shot Learning Using Siamese Networks
This is a highly separated deployment project based on Deepstream , including the full range of Yolo and continuously expanding deployment projects such as Ocr.
This is the research product of the thesis manifold Learning of Latent Space Vectors in GAN for Image Synthesis. This has an application to the research, name a facial recognition system. The application was developed by consulting the FaceNet model.
Who is your doppelgänger and more with Keras face recognition
Real time face recognition Using Facenet , pytorch, Tensorflow
Tensorflow Implementation of FaceNet: A Unified Embedding for Face Recognition and Clustering to find the celebrity whose face matches the closest to yours.
This face recognition system is implemented upon a pre-trained FaceNet model achieving a state-of-the-art accuracy. This system comes with both Live recognition & Image recognition.
A simple face recognition model using pretrained FaceNet model.
Face Recognition and Classification Using FaceNet and MTCNN
This is a simple example for face verification using facenet implemented by davidsandberg
Flutter - Smart Student Attendance App with Facial Recognition
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
About a mobile app created to recognize crime committing citizens from the database and predict using FaceNet prediction algorithm from phone. Admins can create new entries of criminals or notorious people on phone. This will create a safer environment for everyone going to office or airport etc.
Design of a Face recognition payment system prototype
Face Recognition system trained for 81 people. Accuracy is around 70% achieved.
This Flutter project implements face authentication using the FaceNet512 model, storing face data (as Float32 arrays) and names in Firebase Firestore. It allows users to capture and store their face data for subsequent identification, predicting identities based on cosine similarity.
Face Recognition using FaceNet
Building and deploying a Tensorflow (Keras) model for face recognition with Azure ML
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