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BrainCaffe-wiki provide basic information to support your project!

Caffe Documentation - ver.Kor

• 1.Tutorial Documentation : Caffe Tutorial (Kor)

  Practical guide and framework reference.

• 2.Model Zoo : Caffe Model Zoo (Kor)

  BVLC suggests a standard distribution format for Caffe models, and provides trained models.

Caffe Examples - ver.Kor

All of below examples also provided translation for Korean. link for original ones are on translated title beside

• 1.ImageNet Tutorial : Brewing ImageNet (Kor)

  Train and test "CaffeNet" on ImageNet data.

• 2.LeNet MNIST Tutorial : Training LeNet on MNIST with Caffe (Kor)

  Train and test "LeNet" on the MNIST handwritten digit data.

• 3.CIFAR-10 tutorial : Alex’s CIFAR-10 tutorial, Caffe style (Kor)

Train and test Caffe on CIFAR-10 data.

• 4.Fine-tuning for style recognition : Fine-tuning CaffeNet for Style Recognition on “Flickr Style” Data (Kor)

  Fine-tune the ImageNet-trained CaffeNet on the "Flickr Style" dataset.

• 5.Feature extraction with Caffe C++ code : Extracting Features (Kor)

  Extract CaffeNet / AlexNet features using the Caffe utility.

• 6.CaffeNet C++ Classification example : Classifying ImageNet: using the C++ API (Kor)

  A simple example performing image classification using the low-level C++ API.

• 7.Web demo : Web Demo (Kor)

  Image classification demo running as a Flask web server.

• 8.Siamese Network Tutorial : Siamese Network Training with Caffe (Kor)

  Train and test a siamese network on MNIST data.

Analysis of [Pose-v2]

The Analysis of [Pose-v2]'s prototxts will starts soon. it will be attached on wiki too for good example of Caffe Coding.

More information of [Pose-v2], go to project of Structured Feature Learning for Pose Estimation by Xiaogang Wang et al.