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Title: GitHub - DavidSongGitHub/DenseNet: Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award). · GitHub

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X Title: GitHub - DavidSongGitHub/DenseNet: Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).

Description: Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award). - DavidSongGitHub/DenseNet

Open Graph Description: Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award). - DavidSongGitHub/DenseNet

X Description: Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award). - DavidSongGitHub/DenseNet

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85 Commits	https://github.com/DavidSongGitHub/DenseNet/commits/master/
	https://github.com/DavidSongGitHub/DenseNet/commits/master/
datasets	https://github.com/DavidSongGitHub/DenseNet/tree/master/datasets
datasets	https://github.com/DavidSongGitHub/DenseNet/tree/master/datasets
models	https://github.com/DavidSongGitHub/DenseNet/tree/master/models
models	https://github.com/DavidSongGitHub/DenseNet/tree/master/models
LICENSE	https://github.com/DavidSongGitHub/DenseNet/blob/master/LICENSE
LICENSE	https://github.com/DavidSongGitHub/DenseNet/blob/master/LICENSE
README.md	https://github.com/DavidSongGitHub/DenseNet/blob/master/README.md
README.md	https://github.com/DavidSongGitHub/DenseNet/blob/master/README.md
checkpoints.lua	https://github.com/DavidSongGitHub/DenseNet/blob/master/checkpoints.lua
checkpoints.lua	https://github.com/DavidSongGitHub/DenseNet/blob/master/checkpoints.lua
dataloader.lua	https://github.com/DavidSongGitHub/DenseNet/blob/master/dataloader.lua
dataloader.lua	https://github.com/DavidSongGitHub/DenseNet/blob/master/dataloader.lua
main.lua	https://github.com/DavidSongGitHub/DenseNet/blob/master/main.lua
main.lua	https://github.com/DavidSongGitHub/DenseNet/blob/master/main.lua
opts.lua	https://github.com/DavidSongGitHub/DenseNet/blob/master/opts.lua
opts.lua	https://github.com/DavidSongGitHub/DenseNet/blob/master/opts.lua
train.lua	https://github.com/DavidSongGitHub/DenseNet/blob/master/train.lua
train.lua	https://github.com/DavidSongGitHub/DenseNet/blob/master/train.lua
README	https://github.com/DavidSongGitHub/DenseNet
BSD-3-Clause license	https://github.com/DavidSongGitHub/DenseNet
	https://github.com/DavidSongGitHub/DenseNet#densely-connected-convolutional-networks-densenets
Densely Connected Convolutional Networks	http://arxiv.org/abs/1608.06993
Gao Huang	http://www.cs.cornell.edu/~gaohuang/
Zhuang Liu	https://liuzhuang13.github.io/
Laurens van der Maaten	https://lvdmaaten.github.io/
Kilian Weinberger	https://www.cs.cornell.edu/~kilian/
technical report	https://arxiv.org/pdf/1707.06990.pdf
code	https://github.com/liuzhuang13/DenseNet/tree/master/models
fb.resnet.torch	https://github.com/facebook/fb.resnet.torch
	https://github.com/DavidSongGitHub/DenseNet#citation
	https://github.com/DavidSongGitHub/DenseNet#other-implementations
[Caffe]	https://github.com/liuzhuang13/DenseNetCaffe
[Caffe]	https://github.com/Tongcheng/DN_CaffeScript
[PyTorch]	https://github.com/gpleiss/efficient_densenet_pytorch
[PyTorch]	https://github.com/andreasveit/densenet-pytorch
[PyTorch]	https://github.com/bamos/densenet.pytorch
[MXNet]	https://github.com/Nicatio/Densenet/tree/master/mxnet
[MXNet]	https://github.com/bruinxiong/densenet.mxnet
[MXNet]	https://github.com/miraclewkf/DenseNet
[Tensorflow]	https://github.com/YixuanLi/densenet-tensorflow
[Tensorflow]	https://github.com/LaurentMazare/deep-models/tree/master/densenet
[Tensorflow]	https://github.com/ikhlestov/vision_networks
[Lasagne]	https://github.com/Lasagne/Recipes/tree/master/papers/densenet
[Keras]	https://github.com/tdeboissiere/DeepLearningImplementations/tree/master/DenseNet
[Keras]	https://github.com/robertomest/convnet-study
[Keras]	https://github.com/titu1994/DenseNet
[Chainer]	https://github.com/t-hanya/chainer-DenseNet
[Chainer]	https://github.com/yasunorikudo/chainer-DenseNet
[Torch 3D-DenseNet]	https://github.com/barrykui/3ddensenet.torch
	https://github.com/DavidSongGitHub/DenseNet#some-following-up-projects
Multi-Scale Dense Convolutional Networks for Efficient Prediction	https://github.com/gaohuang/MSDNet
DSOD: Learning Deeply Supervised Object Detectors from Scratch	https://github.com/szq0214/DSOD
CondenseNet: An Efficient DenseNet using Learned Group Convolutions	https://github.com/ShichenLiu/CondenseNet
Fully Convolutional DenseNets for Semantic Segmentation	https://github.com/SimJeg/FC-DenseNet
	https://github.com/DavidSongGitHub/DenseNet#contents
Introduction	https://github.com/DavidSongGitHub/DenseNet#introduction
Usage	https://github.com/DavidSongGitHub/DenseNet#usage
Results on CIFAR	https://github.com/DavidSongGitHub/DenseNet#results-on-cifar
Results on ImageNet and Pretrained Models	https://github.com/DavidSongGitHub/DenseNet#results-on-imagenet-and-pretrained-models
Updates	https://github.com/DavidSongGitHub/DenseNet#updates
	https://github.com/DavidSongGitHub/DenseNet#introduction
	https://cloud.githubusercontent.com/assets/8370623/17981494/f838717a-6ad1-11e6-9391-f0906c80bc1d.jpg
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	https://github.com/DavidSongGitHub/DenseNet#usage
here	https://github.com/facebook/fb.resnet.torch/blob/master/INSTALL.md
fb.resnet.torch	https://github.com/facebook/fb.resnet.torch
	https://github.com/DavidSongGitHub/DenseNet#densenet-and-densenet-bc
	https://github.com/DavidSongGitHub/DenseNet#memory-efficient-implementation-newly-added-feature-on-june-6-2017
here	https://github.com/facebook/fb.resnet.torch/blob/master/models/init.lua#L102
here	https://github.com/liuzhuang13/DenseNet/tree/master/models
	https://github.com/DavidSongGitHub/DenseNet#results-on-cifar
	https://github.com/DavidSongGitHub/DenseNet#results-on-imagenet-and-pretrained-models
	https://github.com/DavidSongGitHub/DenseNet#torch
	https://github.com/DavidSongGitHub/DenseNet#models-in-the-original-paper
fb.resnet.torch	https://github.com/facebook/fb.resnet.torch
Download (64.5MB)	https://drive.google.com/open?id=0B8ReS-sYUS-HWFViYlVlZk9sdHc
Download (114.4MB)	https://drive.google.com/open?id=0B8ReS-sYUS-HY25Dc2VrUGlVSGc
Download (161.8MB)	https://drive.google.com/open?id=0B8ReS-sYUS-HaDdpNmlWRjJkd3c
Download (230.8MB)	https://drive.google.com/open?id=0B8ReS-sYUS-HVXp2RExSTmMzZVU
	https://github.com/DavidSongGitHub/DenseNet#models-in-the-tech-report
technical report	https://arxiv.org/pdf/1707.06990.pdf
Download (256MB)	https://drive.google.com/file/d/0By1NwtA2JPGzdVRqOEotMUZrbTA/view?usp=sharing
Download (426MB)	https://drive.google.com/open?id=0By1NwtA2JPGzdkRDaWQ5M3VHTDg
Download (256MB)	https://drive.google.com/file/d/0By1NwtA2JPGzRDhxWGo2a3pOTjA/view?usp=sharing
Download (557MB)	https://drive.google.com/file/d/0By1NwtA2JPGzcnFDSE1HQVh4c0k/view?usp=sharing
	https://github.com/DavidSongGitHub/DenseNet#caffe
https://github.com/shicai/DenseNet-Caffe	https://github.com/shicai/DenseNet-Caffe
	https://github.com/DavidSongGitHub/DenseNet#pytorch
PyTorch documentation on models	http://pytorch.org/docs/torchvision/models.html?highlight=densenet
	https://github.com/DavidSongGitHub/DenseNet#keras-tensorflow-and-theano
https://github.com/flyyufelix/DenseNet-Keras	https://github.com/flyyufelix/DenseNet-Keras
	https://github.com/DavidSongGitHub/DenseNet#mxnet
https://github.com/miraclewkf/DenseNet	https://github.com/miraclewkf/DenseNet
	https://github.com/DavidSongGitHub/DenseNet#wide-densenet-for-better-timeaccuracy-and-memoryaccuracy-tradeoff
wide residual networks	https://github.com/szagoruyko/wide-residual-networks
	https://github.com/DavidSongGitHub/DenseNet#updates
	https://github.com/DavidSongGitHub/DenseNet#contact
Readme	https://github.com/DavidSongGitHub/DenseNet#readme-ov-file
BSD-3-Clause license	https://github.com/DavidSongGitHub/DenseNet#BSD-3-Clause-1-ov-file
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