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

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

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

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

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efficient_densenet_techreport.pdfhttps://github.com/donlyn/DenseNet/blob/master/efficient_densenet_techreport.pdf
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https://github.com/donlyn/DenseNet#densely-connected-convolutional-networks-densenets
"Densely Connected Convolutional Networks"http://arxiv.org/abs/1608.06993
Gao Huanghttp://www.cs.cornell.edu/~gaohuang/
Zhuang Liuhttps://github.com/liuzhuang13
Laurens van der Maatenhttps://lvdmaaten.github.io/
Kilian Weinbergerhttps://www.cs.cornell.edu/~kilian/
technical reporthttps://arxiv.org/pdf/1707.06990.pdf
codehttps://github.com/liuzhuang13/DenseNet/tree/master/models
fb.resnet.torchhttps://github.com/facebook/fb.resnet.torch
https://github.com/donlyn/DenseNet#citing-densenet
https://github.com/donlyn/DenseNet#other-implementations
Caffe Implementationhttps://github.com/liuzhuang13/DenseNetCaffe
Caffe Implementationhttps://github.com/Tongcheng/DN_CaffeScript
PyTorch Implementation (with BC structure)https://github.com/andreasveit/densenet-pytorch
PyTorch Implementation (with BC structure)https://github.com/bamos/densenet.pytorch
MXNet Implementationhttps://github.com/Nicatio/Densenet/tree/master/mxnet
MXNet Implementation (supporting ImageNet)https://github.com/bruinxiong/densenet.mxnet
Tensorflow Implementationhttps://github.com/YixuanLi/densenet-tensorflow
Tensorflow Implementationhttps://github.com/LaurentMazare/deep-models/tree/master/densenet
Tensorflow Implementation (with BC structure)https://github.com/ikhlestov/vision_networks
Lasagne Implementationhttps://github.com/Lasagne/Recipes/tree/master/papers/densenet
Keras Implementationhttps://github.com/tdeboissiere/DeepLearningImplementations/tree/master/DenseNet
Keras Implementationhttps://github.com/robertomest/convnet-study
Keras Implementation (with BC structure)https://github.com/titu1994/DenseNet
Chainer Implementationhttps://github.com/t-hanya/chainer-DenseNet
Chainer Implementationhttps://github.com/yasunorikudo/chainer-DenseNet
https://github.com/donlyn/DenseNet#projects-build-on-densenets
Multi-Scale Dense Convolutional Networks for Efficient Predictionhttps://github.com/gaohuang/MSDNet
Fully Convolutional DenseNets for segmentationhttps://github.com/SimJeg/FC-DenseNet
https://github.com/donlyn/DenseNet#contents
Introductionhttps://github.com/donlyn/DenseNet#introduction
Usagehttps://github.com/donlyn/DenseNet#usage
Results on CIFARhttps://github.com/donlyn/DenseNet#results-on-cifar
Results on ImageNet and Pretrained Modelshttps://github.com/donlyn/DenseNet#results-on-imagenet-and-pretrained-models
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https://github.com/donlyn/DenseNet#introduction
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https://github.com/donlyn/DenseNet#usage
https://github.com/facebook/fb.resnet.torchhttps://github.com/facebook/fb.resnet.torch
fb.resnet.torchhttps://github.com/facebook/fb.resnet.torch
https://github.com/donlyn/DenseNet#densenet-and-densenet-bc
https://github.com/donlyn/DenseNet#memory-efficient-implementation-newly-added-feature-on-june-6-2017
herehttps://github.com/facebook/fb.resnet.torch/blob/master/models/init.lua#L102
herehttps://github.com/liuzhuang13/DenseNet/tree/master/models
https://github.com/donlyn/DenseNet#results-on-cifar
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https://github.com/donlyn/DenseNet#torch
fb.resnet.torchhttps://github.com/facebook/fb.resnet.torch
Download (64.5MB)https://drive.google.com/open?id=0B8ReS-sYUS-HWFViYlVlZk9sdHc
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Download (230.8MB)https://drive.google.com/open?id=0B8ReS-sYUS-HVXp2RExSTmMzZVU
https://github.com/donlyn/DenseNet#caffe
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https://github.com/donlyn/DenseNet#pytorch
PyTorch documentation on modelshttp://pytorch.org/docs/torchvision/models.html?highlight=densenet
code for DenseNethttps://github.com/pytorch/vision/blob/master/torchvision/models/densenet.py
https://github.com/donlyn/DenseNet#keras-tensorflow-and-theano
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https://github.com/donlyn/DenseNet#wide-densenet-for-better-timeaccuracy-and-memoryaccuracy-tradeoff
wide residual networkshttps://github.com/szagoruyko/wide-residual-networks
https://github.com/donlyn/DenseNet#updates
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