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Title: caffe-windows-(1) Download
 Description: caffe for windows. Deep learning framework can be trained for any purpose.
 Downloaders recently: [More information of uploader nasin]
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caffe-windows
.............\.gitignore
.............\3rdparty
.............\........\.gitkeep
.............\CONTRIBUTORS.md
.............\LICENSE
.............\README.md
.............\bin
.............\...\.gitkeep
.............\build
.............\.....\MSVC
.............\.....\....\MainBuilder.sln
.............\.....\....\MainBuilder.vcxproj
.............\.....\MSVCmex
.............\.....\.......\README.txt
.............\.....\.......\bin
.............\.....\.......\...\caffe.mexw64
.............\.....\.......\matcaffe.sln
.............\.....\.......\matcaffe.vcxproj
.............\data
.............\....\cifar10
.............\....\.......\get_cifar10.sh
.............\....\ilsvrc12
.............\....\........\get_ilsvrc_aux.sh
.............\....\mnist
.............\....\.....\get_mnist.sh
.............\docs
.............\....\.gitkeep
.............\....\CNAME
.............\....\README.md
.............\....\_layouts
.............\....\........\default.html
.............\....\cifar10.md
.............\....\development.md
.............\....\feature_extraction.md
.............\....\getting_pretrained_models.md
.............\....\imagenet_training.md
.............\....\index.md
.............\....\installation.md
.............\....\javascripts
.............\....\...........\scale.fix.js
.............\....\mnist.md
.............\....\mnist_prototxt.md
.............\....\mnist_solver_prototxt.md
.............\....\performance_hardware.md
.............\....\stylesheets
.............\....\...........\pygment_trac.css
.............\....\...........\reset.css
.............\....\...........\styles.css
.............\examples
.............\........\MainCaller.cpp
.............\........\cifar10
.............\........\.......\cifar10_full.prototxt
.............\........\.......\cifar10_full_solver.prototxt
.............\........\.......\cifar10_full_solver_lr1.prototxt
.............\........\.......\cifar10_full_solver_lr2.prototxt
.............\........\.......\cifar10_full_test.prototxt
.............\........\.......\cifar10_full_train.prototxt
.............\........\.......\cifar10_quick.prototxt
.............\........\.......\cifar10_quick_solver.prototxt
.............\........\.......\cifar10_quick_solver_lr1.prototxt
.............\........\.......\cifar10_quick_test.prototxt
.............\........\.......\cifar10_quick_train.prototxt
.............\........\.......\convert_cifar_data.cpp
.............\........\.......\create_cifar10.bat
.............\........\.......\create_cifar10.sh
.............\........\.......\get_cifar10_dataset.bat
.............\........\.......\train_full.bat
.............\........\.......\train_full.sh
.............\........\.......\train_quick.bat
.............\........\.......\train_quick.sh
.............\........\feature_extraction
.............\........\..................\imagenet_val.prototxt
.............\........\filter_visualization.ipynb
.............\........\imagenet
.............\........\........\create_imagenet.sh
.............\........\........\get_caffe_reference_imagenet_model.sh
.............\........\........\imagenet_deploy.prototxt
.............\........\........\imagenet_solver.prototxt
.............\........\........\imagenet_train.prototxt
.............\........\........\imagenet_val.prototxt
.............\........\........\make_imagenet_mean.sh
.............\........\........\resume_training.sh
.............\........\........\train_imagenet.sh
.............\........\imagenet_pretrained.ipynb
.............\........\images
.............\........\......\cat.jpg
.............\........\mnist
.............\........\.....\convert_mnist_data.cpp
.............\........\.....\create_mnist.sh
.............\........\.....\get_mnist_leveldb.bat
.............\........\.....\lenet.prototxt
.............\........\.....\lenet_solver.prototxt
.............\........\.....\lenet_test.prototxt
.............\........\.....\lenet_train.prototxt
.............\........\.....\mnist_autoencoder_solver.prototxt
.............\........\.....\mnist_autoencoder_test.prototxt
.............\........\.....\mnist_

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