A review of change detection methods, including codes and open data sets for deep learning. From paper: change detection based on artificial intelligence: state-of-the-art and challenges.

Convert image folder to lmdb, adapted from Efficient-PyTorch

在caffe应用到工程实现时，为了方便系统安装，需要尽可能减少软件的依赖库。 本项目以bash shell/PowerShell脚本实现将caffe依赖的所有第三方库与caffe静态编译一起，以满足全静态编译的要求。 通过本项目提供的脚本生成的caffe编译环境不需要在系统安装任何第三方库和软件，就可以自动完成caffe项目静态编译. 目前在centos6.5/ubuntu16/win7/win10上测试通过,windows上VS2013,VS2015,MinGW 5.2.0编译通过

A Big Awesome List CoreML Models.

Caffe-to-Keras weight converter. Can also export weights as Numpy arrays for further processing.

VGG16 architecture with BatchNorm

Squeeze-and-Excitation Networks

Implemetation of Pyramid Scene Parsing Network in Pytorch

Semantically consistent regularizer for zero-shot learning

The SimNets Architecture's Implementation in Caffe

XNOR-Net, with binary gemm and binary conv2d kernels, support both CPU and GPU.

基于RabbitMQ简单实现验证码识别平台，训练网络模型智能识别图形验证码

Semantic Image Segmentation by Scale-Adaptive Networks (TIP 2019)

Compact Generalized Non-local Network (NIPS 2018)

A Caffe Implementation of SRGAN

Implementation based on the paper Li et al., “A Convolutional Neural Network Cascade for Face Detection, ” 2015 CVPR

Re-implementation of tripletloss function in FaceNet

Depth Map Super-Resolution by Deep Multi-Scale Guidance, ECCV 2016

Mxnet2Caffe_Tensor RT

🎯 保姆级深度学习从入门到放弃 🤪 🤪