深度神经网络资料汇总

 重要的论文：

1. Very deep convolutional networks for large-scale image recognition (VGG-net) (2014) [pdf] [video]

 2. Going deeper with convolutions (GoogLeNet) by Google (2015)              [pdf]        [video]

1. Deep learning (2015)  [pdf]

1. Visualizing and Understanding Convolutional Neural Networks (ZF Net) (2014) [pdf] [video]

1. Fully convolutional networks for semantic segmentation (2015)  [pdf]

1. Deep residual learning for image recognition (ResNet) by Microsoft (2015) [pdf] [video]

1. Deepface: closing the gap to human-level performance in face verification (2014) [pdf] [video]

1. Batch normalization: Accelerating deep network training by reducing internal covariate shift (2015) [pdf]

1. Deep Learning in Neural Networks: An Overview (2015)  [pdf]

10.Delving deep into rectifiers: Surpassing human-level performance on imagenet classification (PReLU) (2014) [pdf]

11.Faster R-CNN: Towards real-time object detection with region proposal networks (2015) [pdf]

12.Fast R-CNN (2015)    [pdf]

13.Spatial pyramid pooling in deep convolutional networks for visual recognition (SPP Net) (2014) [pdf] [video]

14.Generative Adversarial Nets (2014)    [pdf]

15.Spatial Transformer Networks (2015)    [pdf]  [video]

16.Understanding deep image representations by inverting them (2015)    [pdf]

17.Deep Learning of Representations: Looking Forward (2013)    [pdf]

  

经典的文章

ImageNet Classification with Deep Convolutional Neural Networks (AlexNet) (2012) [pdf]

Rectified linear units improve restricted boltzmann machines (ReLU) (2010) [pdf]

   

重要的理论

1. Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images (2015) [pdf]

1. Distilling the Knowledge in a Neural Network (2015)  [pdf]

1. Deep learning in neural networks: An overview (2015)  [pdf]

重要的书籍

• Deep Learning Textbook - An MIT Press book (2016)  [html]

• Learning Deep Architectures for AI  [pdf]

• Neural Nets and Deep Learning  [html]  [github]

重要的课程/Tutorials

• Caffe Tutorial (CVPR 2015)

• Tutorial on Deep Learning for Vision (CVPR 2014)

• Introduction to Deep Learning with Python - Theano Tutorials  [github]

• Deep Learning Tutorials with Theano/Python  [github]

• Deep Learning: Take machine learning to the next level (by udacity)

• DeepLearnToolbox – A Matlab toolbox for Deep Learning  [github]

• Stanford Matlab-based Deep Learning  [github]

• Stanford 231n Class: Convolutional Neural Networks for Visual Recognition [github]

• Deep Learning Course (by Yann LeCun-2016)

• Generative Models (by OpenAI)

• An introduction to Generative Adversarial Networks (with code in TensorFlow)

重要的资源/Models

• VGG-net

• GoogLeNet

• ResNet - MatConvNet implementation

• AlexNet

• Fully Convolutional Networks for Semantic Segmentation

• OverFeat

  

• SPP_net

• Fast R-CNN

• Faster R-CNN

• Generative Adversarial Networks (GANs)

• Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks)

• ResNeXt: Aggregated Residual Transformations for Deep Neural Networks)

• MultiPath Network training code

重要的框架和开发库

• Tensorflow by Google [C++ and CUDA]:  [homepage]  [github]

• Caffe         by          Berkeley         Vision          and         Learning         Center          (BVLC)

[C++]:  [homepage]  [github]  [Installation Instructions]

• Keras by François Chollet [Python]:  [homepage]  [github]

• Microsoft Cognitive Toolkit - CNTK [C++]:  [homepage]  [github]

• MXNet adapted by Amazon [C++]:  [homepage]  [github]

• Torch by Collobert, Kavukcuoglu & Clement Farabet, widely used by Facebook [Lua]: [homepage] [github]

• Convnetjs by Andrej Karpathy [JavaScript]:  [homepage]  [github]

• Theano by Université de Montréal [Python]:  [homepage]  [github]

• Deeplearning4j by startup Skymind [Java]:  [homepage]  [github]

• Paddle by Baidu [C++]:  [homepage]  [github]

• Deep Scalable Sparse Tensor Network Engine (DSSTNE) by Amazon [C++]: [github]

• Neon by Nervana Systems [Python & Sass]:  [homepage]  [github]

• Chainer [Python]:  [homepage]  [github]

• h2o [Java]:  [homepage]  [github]

• Brainstorm by Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA) [Python]: [github]

• Matconvnet by Andrea Vedaldi [Matlab]:  [homepage]  [github]