十、參考文獻 · ApacheCN 深度學習譯文集

# 十、參考文獻 # 第 1 章在這里，我們將學習如何安裝以及 Tensorflow 的基礎知識，作為我們的參考： * <https://www.tensorflow.org/tutorials/> * <https://www.tensorflow.org/install/> # 第 2 章本章將探討機器學習和神經網絡的原理，重點是卷積神經網絡和計算機視覺。本章的參考是： * <https://en.wikipedia.org/wiki/Artificial_neural_network> * <https://en.wikipedia.org/wiki/Timeline_of_machine_learning> * <http://ais.informatik.uni-freiburg.de/teaching/ss11/ki/slides/ai12_acting_under_uncertainty_handout_4up.pdf> * <http://yann.lecun.com/exdb/publis/pdf/lecun-98.pdf> * <https://www.facebook.com/yann.lecun/posts/10152820758292143> * <https://towardsdatascience.com/types-of-convolutions-in-deep-learning-717013397f4d> * <http://cs231n.stanford.edu/> * <http://cs224d.stanford.edu/> # 第 3 章本章將介紹使用深度學習進行的圖像分類，以及為什么 CNN 會干擾我們現在進行計算機視覺的方式。本章的參考是： * [Learning Multiple Layers of Features from Tiny Images](https://www.cs.toronto.edu/~kriz/learning-features-2009-TR.pdf), Alex Krizhevsky, 2009 * 可以在這里找到關于圖像表示技術的出色回顧：*Computer Vision: Algorithms and Applications*, Richard Szeliski, 2010 * <http://www.vision.caltech.edu/Image_Datasets/Caltech101/> * Griffin, Gregory and Holub, Alex and Perona, Pietro (2007) Caltech–256 *Object Category Dataset* * Everingham, M., Van Gool, L., Williams, C. K. I., Winn, J. and Zisserman, *A International Journal of Computer Vision*, 88(2), 303-338, 2010 * *ImageNet Large Scale Visual Recognition Challenge*, IJCV, 2015 * <https://wordnet.princeton.edu/> * *What Does Classifying More Than 10,000 Image Categories Tell Us?* Jia Deng, Alexander C. Berg, Kai Li, and Li Fei-Fei * [Olga Russakovsky, Jia Deng et al. (2015) *ImageNet Large Scale Visual Recognition Challenge*](https://arxiv.org/pdf/1409.0575.pdf) * Alex Krizhevsky, Ilya Sutskever and Geoffrey Hinton,?*ImageNet Classification with Deep Convolutional Neural Networks*, 2012 * <https://arxiv.org/pdf/1311.2901.pdf> * *Going deeper with convolutions*?by Christian Szegedy Google Inc. et al * *Deep Residual Learning for Image Recognition*, Kaiming He et al. * <https://arxiv.org/pdf/1709.01507.pdf> * [批量規范化寫得很好的文章，很容易理解，并且更詳細地解釋了該概念](https://arxiv.org/pdf/1502.03167.pdf) # 第 4 章在本章中，我們將學習對象檢測和分割。本章的參考是： * [*Rich feature hierarchies for accurate object detection and semantic segmentation*](https://arxiv.org/pdf/1311.2524.pdf) * [*Fast RCNN*](https://arxiv.org/pdf/1504.08083.pdf) * [*Faster RCNN Towards Real-Time Object Detection with Region Proposals*](https://arxiv.org/pdf/1506.01497.pdf) * <https://www.youtube.com/watch?v=v5bFVbQvFRk> * [*You Only Look Once: Unified, Real-Time Object Detection*](https://arxiv.org/pdf/1506.02640.pdf) * [Andrew Ng 的深度學習課程](https://coursera.org/specializations/deep-learning) * [*Fully Convolutional Neural Network for Semantic Segmentation*](https://people.eecs.berkeley.edu/~jonlong/long_shelhamer_fcn.pdf) * [Semantic Image Segmentation with?Deep Convolutional Nets, Atrous Convolution,?and Fully Connected CRFs](https://arxiv.org/pdf/1606.00915.pdf) # 第 5 章在本章中，我們將學習一些常見的 CNN 架構（即 VGG，ResNet，GoogleNet）。本章的參考是： * [*Very Deep Convolutional Networks for Large-Scale Image Recognition*](https://arxiv.org/abs/1409.1556),?Simonyan, K. and Zisserman, A., 2014, arXiv preprint arXiv:1409.1556 * [*Going Deeper With Convolutions](https://arxiv.org/abs/1409.4842) * *Deep Residual Learning for Image Recognition*, Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun, Microsoft Research * [*Mobilenets: Efficient Convolutional Neural Networks for Mobile Vision Applications*](https://arxiv.org/abs/1704.04861) * [MobileNets V2](https://arxiv.org/pdf/1801.04381.pdf) # 第 7 章本章將討論遷移學習以及我們如何利用他人的模型訓練來幫助我們訓練自己的網絡。本章的參考是： * <https://www.cse.ust.hk/~qyang/Docs/2009/tkde_transfer_learning.pdf> * <ftp://ftp.cs.wisc.edu/machine-learning/shavlik-group/torrey.handbook09.pdf> * [*CNN Features off-the-shelf: an Astounding Baseline for Recognition*](https://arxiv.org/pdf/1403.6382.pdf) * [*DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition*](https://arxiv.org/pdf/1310.1531.pdf) # 第 9 章在本書的最后一章中，我們將學習如何利用云中的并行計算機集群來加速模型訓練。本章的參考是： * <https://www.oreilly.com/ideas/distributed-tensorflow> * <https://research.fb.com/wp-content/uploads/2017/06/imagenet1kin1h5.pdf> * <https://learningtensorflow.com/lesson11/> * <https://www.tensorflow.org/deploy/distributed> * <https://www.tensorflow.org/programmers_guide/low_level_intro> * <https://github.com/tmulc18/Distributed-TensorFlow-Guide> * <https://clusterone.com/blog/2017/09/13/distributed-tensorflow-clusterone/> * <https://www.youtube.com/watch?v=-h0cWBiQ8s8&> * <https://www.youtube.com/watch?v=uIcqeP7MFH0> * <https://www.youtube.com/watch?v=bRMGoPqsn20> * <https://www.youtube.com/watch?v=1cHx1baKqq0>