Pinned Repositories
Benchmarks-1
常用服务器、数据库、中间件安全配置基线 - 基本包括了所有的操作系统、数据库、中间件、网络设备、浏览器，安卓、IOS、云的安全配置 For benchmarks.cisecurity.org
cnn-models
ImageNet pre-trained models with batch normalization
deep-residual-networks
Deep Residual Learning for Image Recognition
EasyDarwin
open source、high performance、industrial rtsp streaming server,a lot of optimization on streaming relay,KeyFrame cache,RESTful,and web management,also EasyDarwin support distributed load balancing,a simple streaming media cloud platform architecture.高性能开源RTSP流媒体服务器，基于go语言研发，维护和优化：RTSP推模式转发、RTSP拉模式转发、录像、检索、回放、关键帧缓存、秒开画面、RESTful接口、WEB后台管理、分布式负载均衡，基于EasyDarwin构建出了一套基础的流媒体云视频平台架构！
inception
Install-Tensorflow-on-Ubuntu-18.04
Install Tensorflow / Keras on Ubuntu
KungFu
KungFu distributed machine learning framework
Naive-CNN
Take parameters of LeNet from caffe as a pre-trained model.
neural-style
Neural style in TensorFlow! :art:
pytorch_model_summary
pytorch model summary, statistic parameters number, memory usage, FLOPs and so on
jianweilin's Repositories
jianweilin/deep-residual-networks
Deep Residual Learning for Image Recognition
jianweilin/Awesome-Caffe
Awesome Caffe
jianweilin/aws-tensorflow-setup
Install TensorFlow on AWS GPU-instance
jianweilin/C3D
C3D is a modified version of BVLC caffe to support 3D ConvNets.
jianweilin/caffe_dev
try to add weighted loss layer
jianweilin/CaffeCN
caffecn_master
jianweilin/chasing-cats
Scripts and utlities that go with a deployment of Caffe as a cat detector
jianweilin/cnn-benchmarks
Benchmarks for popular CNN models
jianweilin/cnn-text-classification
基于卷积神经网络参数优化的情感分析论文code
jianweilin/crfasrnn
This repository contains the source code for the semantic image segmentation method described in the ICCV 2015 paper: Conditional Random Fields as Recurrent Neural Networks. http://crfasrnn.torr.vision/
jianweilin/deep-visualization-toolbox
DeepVis Toolbox
jianweilin/DeepDarkFantasy
jianweilin/DeepLearnToolbox
Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.
jianweilin/DIGITS
Deep Learning GPU Training System
jianweilin/dilation
Dilated Convolution for Semantic Image Segmentation
jianweilin/Face-Resources
jianweilin/FaceVerification
An Experimental Implementation of Face Verification, 96.8% on LFW.
jianweilin/FasterRCNN-Encapsulation-Cplusplus
Encapsulation C++ version of FasterRCNN
jianweilin/FastPredictiveImageRegistration
Source code for X. Yang et al., "Fast Predictive Image Registration"
jianweilin/fooling
Code base for "Deep Neural Networks are Easily Fooled" CVPR 2015 paper
jianweilin/himawaripy
Set near-realtime picture of Earth as your desktop background
jianweilin/LCNN_TRAIN
train model of "A Lightened CNN for Deep Face Representation" 人脸识别
jianweilin/matlab-lmdb
Matlab LMDB wrapper
jianweilin/py-faster-rcnn
Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version
jianweilin/ResNet-on-Cifar10
Reimplementation ResNet on cifar10
jianweilin/ResNet-Prototxt-for-Caffe
Generator of ResNet on CIFAR
jianweilin/SqueezeNet
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters
jianweilin/t-sne
t-distributed Stochastic Neighbour Embedding (t-SNE)
jianweilin/tensorflow_install_commands
jianweilin/twostreamfusion
Code release for "Convolutional Two-Stream Network Fusion for Video Action Recognition", CVPR 2016.