AmemiyaYuko's starred repositories
cleverhans
An adversarial example library for constructing attacks, building defenses, and benchmarking both
object-recognition
Data and materials from the paper "Comparing deep neural networks against humans: object recognition when the signal gets weaker" (arXiv 2017)
Super-Resolution.Benckmark
Benchmark and resources for single super-resolution algorithms
GuidedFilter
Simple python demos of Guided Image Filtering (Python).
SRCNN-Tensorflow
Image Super-Resolution Using Deep Convolutional Networks in Tensorflow https://arxiv.org/abs/1501.00092v3
DCGAN-tensorflow
A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"
Deformable-ConvNets
Deformable Convolutional Networks
tensorflow-adversarial
Crafting adversarial images
deep_complex_networks
Implementation related to the Deep Complex Networks
GlobalSIP16-OWA
Image Aesthetuc Assessment via Deep Semantic Aggregation (GlobalSIP16)
improved_wgan_training
Code for reproducing experiments in "Improved Training of Wasserstein GANs"
tensorflow-101
learn code with tensorflow
Generative-Adversarial-Network-Tutorial
Tutorial on creating your own GAN in Tensorflow
deeplearningbook-chinese
Deep Learning Book Chinese Translation
BEGAN-tensorflow
Tensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"
handwriting
Chinese Handwriting Recognition with CNNs
cnn-text-classification-tf-chinese
CNN for Chinese Text Classification in Tensorflow
adversarial
Code and hyperparameters for the paper "Generative Adversarial Networks"
Faster-High-Res-Neural-Inpainting
High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesis
WassersteinGAN.tensorflow
Tensorflow implementation of Wasserstein GAN - arxiv: https://arxiv.org/abs/1701.07875
Seq2Seq_Chatbot_QA
使用TensorFlow实现的Sequence to Sequence的聊天机器人模型
AdversarialNetsPapers
Awesome paper list with code about generative adversarial nets
stanford_dl_ex
Programming exercises for the Stanford Unsupervised Feature Learning and Deep Learning Tutorial