face detection, verification and recognition using Keras
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Updated
Feb 21, 2018 - Python
face detection, verification and recognition using Keras
CNN
即時人臉辨識(使用OpenCV與FaceNet)
Convolutional Neural Networks repository for all projects of Course 4 of 5 of the Deep Learning Specialization covering CNNs and classical architectures like LeNet-5, AlexNet, GoogleNet Inception Network, VGG-16, ResNet, 1x1 Convos, OverFeat, R-CNN, Fast R-CNN, Faster R-CNN, YOLO, YOLO9000, DeepFace, FaceNet and Neural Style Transfer.
This project is designed for one shot face identify people in video
Contains all the Frameworks and Models from Scratch being used for Facial Recognition.
AI thesis regarding syndrome vs. control classification of faces of people with Intellectual Disability.
A system of neural networks to detect and recognize faces. We use techniques developed in FaceNet and DeepFace for face recognition and create a simplified YOLO algorithm for face detection.
CMP5103 - Artificial Intelligence - Emotion Recognition & Report
Simple face gender detection for an online meeting (e.g. Zoom or Microsoft Teams). The application is modified based on face-emotion: https://github.com/DeepSE/face-emotion
facialAnalysisDetection2D: Detector implementation for the analysis of facial features. Using the deepFace API, analysis for the extraction and prediction of gender, age, ethnicity and emotions. Image source reception via YARP, processing and sending of detections via YARP port.
This project is based on deepface python library.
Development of a Real-Time Emotion Recognition System Using Facial Expressions and EEG based on machine learning and deep neural network methods
Partly unfinished racial recognition project made using the power of **Python** that can detect a face on in a camera feed and analyze it using DeepFace
The aim of the project is to recommend Spotify songs based on emotions detected.
Keras implementation of the renowned publication "DeepFace: Closing the Gap to Human-Level Performance in Face Verification" by Taigman et al. Pre-trained weights on VGGFace2 dataset.
This project presents a systems integration, where it is possible to determine emotions from human faces.
Face detection and facial feature analysis application using streamlit, opencv and deepface.
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