MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)
This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
Handbooks and Code Samples for Software Engineers wanting to learn the Keras Machine Learning framework
A CNN based pytorch implementation on facial expression recognition (FER2013 and CK+), achieving 73.112% (state-of-the-art) in FER2013 and 94.64% in CK+ dataset
Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.
Real-time face detection and emotion/gender classification using fer2013/imdb datasets and openCV.
This code is using FER2013 dataset with keras library and tensorflow backend. This code was fork and modified for keras with tensorflow backend from https://github.com/LamUong/FacialExpressionRecognition
Face expression recognition app with Keras, Flask and OpenCV
