神經網路學習參考

轉自https://blog.csdn.net/l297969586/article/details/71159675

vm配置：http://blog.csdn.net/u013142781/article/details/50529030 

CMakeLists.txt： http://blog.csdn.net/z_h_s/article/details/50699905 
莫煩python： https://morvanzhou.github.io/ 
廖雪峰git與python： https://www.liaoxuefeng.com/ 
～～ios上實現小規模yolo模型： http://colabug.com/107304.html 
影像檢測彙總： https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html#t-cnn 
壓縮caffemodel： https://github.com/RalphMao/demo_nn_compress 
實時車輛檢測： https://github.com/upul/CarND-Vehicle-Detection 
MPII行人位姿資料集，可PK： http://human-pose.mpi-inf.mpg.de/#overview 
識別領域彙總： http://www.cnblogs.com/zlslch/p/6970680.html 
xnor採訪名言: https://techcrunch.com/2017/01/19/xnor-ai-frees-ai-from-the-prison-of-the-supercomputer/ 
部落格專欄： http://blog.csdn.net/column/mycolumn.html 
多人位姿檢測（骨骼點）2017： https://github.com/ZheC/Realtime_Multi-Person_Pose_Estimation 
github 57個最火熱的框架： http://www.oschina.net/news/79500/57-most-popular-deep-learning-project-at-github

0、以後有用

Boosted Tree：一篇很有見識的文章 http://dataunion.org/15787.html 
Kaggle—So Easy!百行程式碼實現排名Top 5%的影像分類比賽 ： 
http://blog.csdn.net/v_july_v/article/details/71598551 
卷積的尺度和位置不變形解析：https://www.quora.com/How-is-a-convolutional-neural-network-able-to-learn-invariant-features

1.LSTM與RNN

官方:http://colah.github.io/posts/2015-08-Understanding-LSTMs/ 
翻譯:http://www.jianshu.com/p/9dc9f41f0b29 
cs231n老師的部落格:http://karpathy.github.io/2015/05/21/rnn-effectiveness/ 
這個是我見得寫的最好的RNN，裡面還有關於機器翻譯，語音識別，語言模式，影像描述的論文，絕了：http://blog.csdn.net/heyongluoyao8/article/details/48636251 
影像描述論文（cs231n的Andrej Karpathy）與github程式碼地址： 
http://cs.stanford.edu/people/karpathy/deepimagesent/ 
https://github.com/karpathy/neuraltalk

2.YOLO2訓練自己的資料集

http://lib.csdn.net/article/deeplearning/57863?knId=1726 
http://blog.csdn.net/samylee/article/details/53414108 
V1版:http://blog.csdn.net/sinat_30071459/article/details/53100791

3.faster訓練自己的資料集

http://blog.csdn.net/sinat_30071459/article/details/51332084 
http://blog.csdn.net/sinat_30071459/article/details/50723212

4、深度學習

類似cs231n：http://blog.csdn.net/u014595019/article/details/52571966 
大牛：http://blog.csdn.net/xbinworld/article/details/44464663 
大牛！全：http://blog.csdn.net/hjimce/article/details/49255013 
基礎深度學習，有程式碼： 
https://www.zybuluo.com/hanbingtao/note/433855 
Deep Learning Tutorials 
http://www.deeplearning.net/tutorial/ 
BN層原理：http://www.cnblogs.com/stingsl/p/6428694.html

5.Theano學習

學習指南翻譯（版本1）： 
http://www.cnblogs.com/xueliangliu/archive/2013/04/03/2997437.html 
學習指南翻譯（版本2）： 
http://www.cnblogs.com/charleshuang/p/3648804.html 
官方： 
http://deeplearning.net/software/theano/tutorial/ 
★github示例： 
https://github.com/Newmu/Theano-Tutorials 
★挺全的theano知識點講解 
http://www.cnblogs.com/shouhuxianjian/category/699462.html 
theano函式官方文件： 
http://deeplearning.net/software/theano/library/tensor/basic.html 
簡單易懂： 
http://www.cnblogs.com/YiXiaoZhou/p/6079428.html 
keras官方文件：http://keras-cn.readthedocs.io/en/latest/

6.python基礎

super：http://www.cnblogs.com/lovemo1314/archive/2011/05/03/2035005.html 
format:http://www.jb51.net/article/63672.htm 
anaconda安裝tensorflow： 
http://www.cnblogs.com/aloiswei/p/6510355.html

7.lua

lua物件導向程式設計，寫的很透徹： 
http://www.jellythink.com/archives/529 
.與：區別： 
http://www.cnblogs.com/youxilua/archive/2011/07/28/2119059.html 
元表方法： 
http://www.cnblogs.com/JimLy-BUG/p/5364281.html

8.mxnet

https://github.com/dmlc/mxnet 
BMNet：https://github.com/hpi-xnor/BMXNet

9.torch

卷積層原始碼：http://blog.csdn.net/shenxiaolu1984/article/details/52373174 
tensor操作：http://blog.csdn.net/whgyxy/article/details/52204206 
60分鐘學torch： 
原版：https://github.com/soumith/cvpr2015/blob/master/Deep%20Learning%20with%20Torch.ipynb 
翻譯：http://blog.csdn.net/baidu_17806763/article/details/61630538 
torch學習資料：http://blog.csdn.net/victoriaw/article/details/71703568 
torch學習系列（1），包含tensor操作：http://blog.csdn.net/whgyxy/article/category/6352333 
torch學習系列（2）http://blog.csdn.net/u010946556/article/category/6216156 
torch.nn模組學習（還有tensorflow、matlab、softmax問題）：http://blog.csdn.net/hejunqing14/article/category/6356970 
torch學習系列（3）：http://blog.csdn.net/Hungryof/article/category/6245605 
torch、自己建立一個層（如xnor）：https://zhuanlan.zhihu.com/p/21550685 
官方：http://torch.ch/docs/developer-docs.html 
一些torch小函式：http://blog.csdn.net/JIEJINQUANIL/article/category/5884857 
關於torch建立層彙總： 
http://blog.csdn.net/lanran2/article/details/50494570 
http://lib.csdn.net/article/deeplearning/51259 
http://www.cnblogs.com/crossing/p/4826668.html 
http://torch.ch/docs/developer-docs.html

10.Tensorflow-faster

tensorflow與Keras（Keras中文官方文件）：https://keras-cn.readthedocs.io/en/latest/blog/keras_and_tensorflow/ 
Tensorflow-API：https://www.tensorflow.org/api_docs/ 
Faster-RCNN_TF:https://github.com/smallcorgi/Faster-RCNN_TF 
tf-faster-rcnn:https://github.com/endernewton/tf-faster-rcnn 
將tensorflow移植到android手機實現物體識別！！http://blog.csdn.net/xiaopihaierletian/article/details/61933695
tensorflow-API：http://www.jianshu.com/nb/5517733 
常用函式：http://blog.csdn.net/lenbow/article/details/52152766 
tensorflow基礎學習部落格：http://blog.csdn.net/u012436149/article/details/53018924 
tensorflow應用較全：http://blog.csdn.net/helei001/article/details/51842531

11、faster

http://blog.csdn.net/wopawn/article/details/52223282 
demo.py解析 
論文解析，很好：http://blog.csdn.net/wopawn/article/details/52223282#reply 
論文翻譯，這人有一套rcnn部落格：http://blog.csdn.net/u011534057/article/details/51259812 
overfeat：http://blog.sciencenet.cn/blog-1583812-844178.html 
rpn程式碼解析：http://blog.csdn.net/sloanqin/article/details/51545125

12、安裝tcl/tk和Tkinter

http://blog.csdn.net/cryhelyxx/article/details/22514871

13、在閱讀Faster-RCNN_TF程式碼中觀看的部落格：

os.path:http://book.51cto.com/art/201405/440066.htm 
eastdict:https://pypi.python.org/pypi/easydict/ 
strip:http://www.cnblogs.com/itdyb/p/5046472.html 
zip:http://www.cnblogs.com/frydsh/archive/2012/07/10/2585370.html 
range與xrange:http://blog.csdn.net/ithomer/article/details/17285449 
xml.etree.ElementTree:http://www.cnblogs.com/hongten/p/hongten_python_xml_etree_elementtree.html 
xml檔案解析：http://blog.csdn.net/zhangjunbob/article/details/52769381 
http://blog.csdn.net/gingerredjade/article/details/21944675 
@作用：http://blog.sina.com.cn/s/blog_571b19a001013h7j.html 
stack:http://blog.csdn.net/huruzun/article/details/39801217 
generate_anchors.py註釋:http://blog.csdn.net/xzzppp/article/details/52317863 
numpy.ravel() vs numpy.flatten() :http://blog.csdn.net/lanchunhui/article/details/50354978 
meshgrid:http://blog.csdn.net/grey_csdn/article/details/69663432 
anchor產生的問題：http://blog.csdn.net/zqjackking/article/details/59725989 
bbox.pyx：http://blog.csdn.net/guotong1988/article/details/54729530 
tf.nn.softmax_cross_entropy_with_logits：http://blog.csdn.net/mao_xiao_feng/article/details/53382790 
tensor與ndarray操作與轉換：http://blog.csdn.net/wyl1987527/article/details/62458057 
★變數、相關變數初始化、儲存：http://www.cnblogs.com/claude-gyh/p/6554322.html 
saver：http://blog.csdn.net/u011500062/article/details/51728830 
uninitial error:https://stackoverflow.com/questions/34001922/failedpreconditionerror-attempting-to-use-uninitialized-in-tensorflow 
★與模型儲存讀取（saver）相關的一切操作：http://cv-tricks.com/tensorflow-tutorial/save-restore-tensorflow-models-quick-complete-tutorial/ 
翻譯：http://blog.163.com/wujiaxing009@126/blog/static/7198839920175671529472/ 
其餘相關：http://www.cnblogs.com/azheng333/archive/2017/06/09/6972619.html 
http://blog.csdn.net/thriving_fcl/article/details/71423039 
http://www.jianshu.com/p/8487db911d9a 
http://blog.csdn.net/u014659656/article/details/53954793 
tf.trainable_variables與tf.all_variables:http://blog.csdn.net/uestc_c2_403/article/details/72356448 
tf.gradients 與 tf.stop_gradient() :http://blog.csdn.net/u012436149/article/details/53905797

14、haar與adaboost

利用OpenCV自帶的haar training程式訓練分類器 ：http://blog.csdn.net/carson2005/article/details/8171571 
http://blog.csdn.net/liulina603/article/details/8184451 
haar原理：http://www.cnblogs.com/ello/archive/2012/04/28/2475419.html 
http://blog.csdn.net/bbzz2/article/details/50764159 
dlib+opencv人臉特徵檢測：http://blog.csdn.net/zmdsjtu/article/details/52422847 
訓練常見問題：http://www.cnblogs.com/chensheng-zhou/p/5542887.html

15、dlib array2d與Mat

https://stackoverflow.com/questions/29118317/how-to-convert-mat-to-array2drgb-pixel 
http://blog.csdn.net/huixingshao/article/details/55510950 
http://blog.csdn.net/qq_26671711/article/details/53713529 
http://blog.csdn.net/yubin1277408629/article/details/53561037

16、三維重建

vcglib -github：https://github.com/cnr-isti-vclab/vcglib 
win10+vs+cuda ：http://blog.csdn.net/u011821462/article/details/50145221 
★三維視覺化工程：http://redwood-data.org/indoor/tutorial.html 
win10+vs2015 meshlab編譯 ：http://blog.csdn.net/hanshuobest/article/details/71525388 
windows-git：http://blog.csdn.net/qq_34698126/article/details/53521187

17、kinfu環境配置

kinfu安裝配置全解：http://blog.csdn.net/alan_1550587588/article/details/54582192 
VS2010和IVF2011的安裝教程 Fortran： 
http://wenku.baidu.com/view/9e28de1b01f69e314332949c.html 
Fortran認證照Intel_Visual_Fortran_XE2011.lic： 
http://pan.baidu.com/s/1kT9lR8r 
ros下使用kinfu：http://blog.csdn.net/l_h2010/article/details/38349927

18、c++

c++筆記：http://www.cnblogs.com/ggjucheng/archive/2012/08/18/2645319.html 
typedef：http://blog.csdn.net/ameyume/article/details/6326278 
指標的指標：http://blog.jobbole.com/60647/ 
成員函式指標：http://blog.csdn.net/jinjinclouded/article/details/5189540 
c++指標：http://www.cnblogs.com/ggjucheng/archive/2011/12/13/2286391.html 
qt學習：http://www.kuqin.com/qtdocument/tutorial.html 
argc和argv含義及用法 ：http://blog.csdn.net/dcrmg/article/details/51987413 
虛擬函式與純虛擬函式：http://blog.csdn.net/xwpc702/article/details/8670025 
http://blog.csdn.net/hackbuteer1/article/details/7558868

19、ELL

安裝中出現問題解決（中文）部落格：https://www.codelast.com/%e5%8e%9f%e5%88%9b-%e5%9c%a8ubuntu-14-04%e7%b3%bb%e7%bb%9f%e4%b8%ad%e4%b8%baell%e5%ae%89%e8%a3%85python-3-6-%e9%80%9a%e8%bf%87miniconda/ 
https://www.codelast.com/%e5%8e%9f%e5%88%9b-%e5%9c%a8%e6%a0%91%e8%8e%93%e6%b4%be3%e4%b8%8a%e4%bd%bf%e7%94%a8%e5%be%ae%e8%bd%afell%e5%b5%8c%e5%85%a5%e5%bc%8f%e5%ad%a6%e4%b9%a0%e5%ba%931/

20、光流測速度

http://blog.csdn.net/chentravelling/article/details/50924144 
http://blog.csdn.net/taily_duan/article/details/51011288 
http://blog.csdn.net/zouxy09/article/details/8683859 
http://blog.csdn.net/dcrmg/article/details/52684477 
http://blog.csdn.net/crzy_sparrow/article/details/7407604 
載入深度資訊求速度原理： 

21、識別走過的彎路：

【人體姿態】Stacked Hourglass演算法詳解 （torch程式碼）：http://blog.csdn.net/shenxiaolu1984/article/details/51428392 
Object Detection︱RCNN、faster-RCNN框架的淺讀與延伸內容筆記 ： 
http://blog.csdn.net/roslei/article/details/73459873 
ipython-notebook caffe識別與視覺化：http://nbviewer.jupyter.org/github/BVLC/caffe/blob/master/examples/00-classification.ipynb#Classification:-Instant-Recognition-with-Caffe

22、語義分割與識別

FCN-github：https://github.com/shelhamer/fcn.berkeleyvision.org 
fcn-知乎：https://zhuanlan.zhihu.com/p/22976342 
FCN-CRF：https://zhuanlan.zhihu.com/p/22308032

23、deep compression與SqueezeNet

SqueezeNet-github:https://github.com/DeepScale/SqueezeNet 
Deep Compression閱讀理解及Caffe原始碼修改 ：http://blog.csdn.net/may0324/article/details/52935869 
閱讀理解： 
http://blog.csdn.net/zijin0802034/article/details/53982812 
http://blog.csdn.net/boon_228/article/details/51718521 
http://blog.csdn.net/cyh_24/article/details/51708469 
http://blog.csdn.net/joshuaxx316/article/details/52514978 
壓縮caffemodel：https://github.com/RalphMao/demo_nn_compress 
SqueezeNet+Faster-RCNN+OHEM：http://blog.csdn.net/u011956147/article/details/53714616

24、TFFRCNN（基於Faster-RCNN_TF修改）

https://github.com/CharlesShang/TFFRCNN，內含PVANET模型 
執行TFFRCNN：http://blog.csdn.net/yuexin2/article/details/75019330 
TFRRCNN訓練自己的模型：http://blog.csdn.net/yuexin2/article/details/75025720

25、嵌入式網路

CNN 模型壓縮與加速演算法綜述 :http://blog.csdn.net/QcloudCommunity/article/details/77719498 
YOLO對比SVM+HOG 耗時更短 處理更精確（附github資源）：http://www.weiot.net/article-59672.html 
LCDet：http://blog.csdn.net/zhangjunhit/article/details/72831440 
PVANet（TFFRCNN中有）：https://arxiv.org/pdf/1608.08021.pdf 
http://blog.csdn.net/wydbyxr/article/details/68931337 
mobilenet：http://blog.csdn.net/zchang81/article/details/73321202 
//（有實現連結）http://blog.csdn.net/mao_feng/article/details/75116085 
//論文翻譯：https://baijiahao.baidu.com/s?id=1566004753349359&wfr=spider&for=pc 
ARM-NEON：http://blog.csdn.net/qiek/article/details/50900890 
http://blog.csdn.net/ljp12345/article/details/53490094 
popcnt：http://www.cnblogs.com/zyl910/archive/2012/11/02/testpopcnt.html

26、有用知乎

https://www.zhihu.com/question/39921464 
https://www.zhihu.com/question/53697001 
https://www.zhihu.com/question/27872849

27.卷積加速相關

http://blog.csdn.net/mao_kun/article/details/54882528 
http://blog.csdn.net/u010620604/article/details/52464529

28.CMakeLists

http://www.360doc.com/content/12/0507/10/9369336_209205930.shtml 
http://blog.csdn.net/zhubaohua_bupt/article/details/52760411

29.強化學習

david 9:http://nooverfit.com/wp/15-%E5%A2%9E%E5%BC%BA%E5%AD%A6%E4%B9%A0101-%E9%97%AA%E7%94%B5%E5%85%A5%E9%97%A8-reinforcement-learning/ 
精彩:http://www.cnblogs.com/jinxulin/p/3517377.html 
知乎大神:https://www.zhihu.com/question/41775291

30、3D-deeplearning-face_detector

https://zhuanlan.zhihu.com/p/24816781

31、xnor相關工程與討論

https://github.com/allenai/XNOR-Net/issues 
https://github.com/jiecaoyu/XNOR-Net-PyTorch 
https://github.com/tensorflow/tensorflow/issues/1592 
https://github.com/MatthieuCourbariaux/BinaryNet 
https://github.com/loswensiana/BWN-XNOR-caffe/tree/master/examples/imagenet 
https://github.com/tensorflow/tensorflow/tree/master/third_party/eigen3/unsupported/Eigen/CXX11/src/FixedPoint 
☆修改梯度相關 http://blog.csdn.net/buyi_shizi/article/details/51512848 
http://blog.csdn.net/yihaizhiyan/article/details/44159063

32、FCN訓練自己的資料集

詳細版本：http://blog.csdn.net/jiongnima/article/details/78549326?locationNum=1&fps=1 
http://blog.csdn.net/zoro_lov3/article/details/74550735 
http://blog.csdn.net/z13653662052/article/details/70949440 
http://blog.csdn.net/supe_king/article/details/58121993 
http://blog.csdn.net/u010402786/article/details/72883421 
http://www.cnblogs.com/xuanxufeng/p/6243342.html 
https://github.com/315386775/FCN_train 
https://github.com/msracver/FCIS

33、伺服器搭建

http://blog.csdn.net/totodum/article/details/51059380 
http://blog.csdn.net/fishman_yinwang/article/details/78029309 
http://blog.csdn.net/jiaojialulu/article/details/77430563 
34、推薦系統 
https://github.com/jfkirk/tensorrec 
https://github.com/bnak/Recommendations_Engine 
https://github.com/songgc/TF-recomm 
https://github.com/sonyisme/keras-recommendation 
https://github.com/geeky-bit/Recommendation_systems-using-SVD-KNN-etc 
https://github.com/amzn/amazon-dsstne 
recommendation decomposition

https://www.douban.com/note/510047571/ 
https://github.com/Lockvictor/MovieLens-RecSys

http://blog.csdn.net/u011467621/article/details/48624973 
https://github.com/joeyqzhou/recommendation-system

講解：http://blog.csdn.net/joycewyj/article/details/51692976

https://github.com/chengstone/movie_recommender 
http://blog.csdn.net/chengcheng1394/article/details/78820529

35、caffe

https://github.com/loswensiana/BWN-XNOR-caffe 
新增新層： 
https://blog.csdn.net/shuzfan/article/details/51322976（cutoff） 
https://blog.csdn.net/wfei101/article/details/76735760（盜版） 
https://blog.csdn.net/kuaitoukid/article/details/41865803（maxout與NIN） 
https://blog.csdn.net/xizero00/article/details/52529341（影像縮放） 
https://blog.csdn.net/happyflyy/article/details/54866037（maxout） 
caffe函式解析： 
https://blog.csdn.net/seven_first/article/details/47378697

caffe卷積實現原理： 
https://blog.csdn.net/jiongnima/article/details/69055941 
im2col原理： 
https://blog.csdn.net/jiongnima/article/details/69736844