自己有用的博客

Myth丶恋晨 2022-06-16 03:40 2670阅读 0赞

2018 paper:https://github.com/amusi/daily-paper-computer-vision  
人数统计：https://github.com/gjy3035/Awesome-Crowd-Counting  
pytorch中文文档：https://ptorch.com/news/53.html  
mac-shell 配置：https://www.jianshu.com/p/405956cdaca6  
docker-安装cuda9-cudnn7：https://blog.csdn.net/u012939880/article/details/82887985  
一文读懂BN：https://www.cnblogs.com/makefile/p/batch-norm.html?utm\_source=debugrun&utm\_medium=referral  
docker:https://blog.csdn.net/elaine\_bao/article/details/53117676  
BN层还可添加：https://blog.csdn.net/qq\_29573053/article/details/79878437  
roofline:https://zhuanlan.zhihu.com/p/34204282  
BN层融合：https://www.cnblogs.com/nowgood/p/juan-ji-ceng-he-liang-hua-ceng-rong-he.html  
读caffe源码过程：https://www.cnblogs.com/ycjing/p/5281384.html  
MPI多进程：https://blog.csdn.net/zouxy09/article/details/49031845\#commentBox  
标注工具汇总：https://blog.csdn.net/chaipp0607/article/details/79036312  
108关键点人脸识别：https://github.com/zeusees/HyperLandmark  
vm配置：http://blog.csdn.net/u013142781/article/details/50529030  
CMakeLists.txt：http://blog.csdn.net/z\_h\_s/article/details/50699905  
莫烦python：https://morvanzhou.github.io/  
廖雪峰git与python：https://www.liaoxuefeng.com/  
～～ios上实现小规模yolo模型：http://colabug.com/107304.html  
图像检测汇总：https://handong1587.github.io/deep\_learning/2015/10/09/object-detection.html\#t-cnn  
压缩caffemodel：https://github.com/RalphMao/demo\_nn\_compress  
实时车辆检测：https://github.com/upul/CarND-Vehicle-Detection  
MPII行人位姿数据集，可PK：http://human-pose.mpi-inf.mpg.de/\#overview  
识别领域汇总：http://www.cnblogs.com/zlslch/p/6970680.html  
xnor采访名言:https://techcrunch.com/2017/01/19/xnor-ai-frees-ai-from-the-prison-of-the-supercomputer/  
博客专栏：http://blog.csdn.net/column/mycolumn.html  
多人位姿检测（骨骼点）2017：https://github.com/ZheC/Realtime\_Multi-Person\_Pose\_Estimation  
github 57个最火热的框架：http://www.oschina.net/news/79500/57-most-popular-deep-learning-project-at-github  
人脸检测、arm加速caffe：https://github.com/OAID/FaceRecognition  
关于人脸检测的几个框架:http://www.sohu.com/a/154168717\_206784  
聊天机器人：https://www.cnblogs.com/zdz8207/p/DeepLearning-tensorflow-chatbot.html  
大牛：http://www.shareditor.com/blogshow/?blogId=121  
语料数据集 https://github.com/candlewill/Dialog\_Corpus  
各种数据集:https://zhuanlan.zhihu.com/p/25138563  
车辆检测（RepNet）：https://github.com/xuqiantong/RepNet  
反卷积：https://www.zhihu.com/question/43609045  
条形码检测识别：https://github.com/seajune/Barcode-Scanner  
CVPR 2018：http://openaccess.thecvf.com/CVPR2018.py  
BN层讲解：https://blog.csdn.net/myarrow/article/details/51848285  
sotfmax BP：https://www.cnblogs.com/alexanderkun/p/8098781.html  
inception v1-v4:  
http://baijiahao.baidu.com/s?id=1601882944953788623&wfr=spider&for=pc  
https://blog.csdn.net/wspba/article/details/68065564  
mongo db:https://www.yiibai.com/mongodb/mongodb\_python.html  
mqtt协议：https://www.jianshu.com/p/5c42cb0ed1e9

## 0、以后有用 ##

Boosted Tree：一篇很有见识的文章 http://dataunion.org/15787.html  
Kaggle—So Easy!百行代码实现排名Top 5%的图像分类比赛 ：  
http://blog.csdn.net/v\_july\_v/article/details/71598551  
卷积的尺度和位置不变形解析：https://www.quora.com/How-is-a-convolutional-neural-network-able-to-learn-invariant-features

## 1.LSTM与RNN ##

官方:[http://colah.github.io/posts/2015-08-Understanding-LSTMs/][http_colah.github.io_posts_2015-08-Understanding-LSTMs]  
翻译:[http://www.jianshu.com/p/9dc9f41f0b29][http_www.jianshu.com_p_9dc9f41f0b29]  
cs231n老师的博客:[http://karpathy.github.io/2015/05/21/rnn-effectiveness/][http_karpathy.github.io_2015_05_21_rnn-effectiveness]  
这个是我见得写的最好的RNN，里面还有关于机器翻译，语音识别，语言模式，图像描述的论文，绝了：[http://blog.csdn.net/heyongluoyao8/article/details/48636251][http_blog.csdn.net_heyongluoyao8_article_details_48636251]  
图像描述论文（cs231n的Andrej Karpathy）与github代码地址：  
[http://cs.stanford.edu/people/karpathy/deepimagesent/][http_cs.stanford.edu_people_karpathy_deepimagesent]  
[https://github.com/karpathy/neuraltalk][https_github.com_karpathy_neuraltalk]

## 2.YOLO2训练自己的数据集 ##

[http://lib.csdn.net/article/deeplearning/57863?knId=1726][http_lib.csdn.net_article_deeplearning_57863_knId_1726]  
[http://blog.csdn.net/samylee/article/details/53414108][http_blog.csdn.net_samylee_article_details_53414108]  
V1版:[http://blog.csdn.net/sinat\_30071459/article/details/53100791][http_blog.csdn.net_sinat_30071459_article_details_53100791]

## 3.faster训练自己的数据集 ##

http://blog.csdn.net/sinat\_30071459/article/details/51332084  
http://blog.csdn.net/sinat\_30071459/article/details/50723212

## 4、深度学习 ##

类似cs231n：[http://blog.csdn.net/u014595019/article/details/52571966][http_blog.csdn.net_u014595019_article_details_52571966]  
大牛：[http://blog.csdn.net/xbinworld/article/details/44464663][http_blog.csdn.net_xbinworld_article_details_44464663]  
大牛！全：[http://blog.csdn.net/hjimce/article/details/49255013][http_blog.csdn.net_hjimce_article_details_49255013]  
基础深度学习，有代码：  
[https://www.zybuluo.com/hanbingtao/note/433855][https_www.zybuluo.com_hanbingtao_note_433855]  
Deep Learning Tutorials  
[http://www.deeplearning.net/tutorial/][http_www.deeplearning.net_tutorial]  
BN层原理：http://www.cnblogs.com/stingsl/p/6428694.html

## 5.Theano学习 ##

学习指南翻译（版本1）：  
http://www.cnblogs.com/xueliangliu/archive/2013/04/03/2997437.html  
学习指南翻译（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知识点讲解  
http://www.cnblogs.com/shouhuxianjian/category/699462.html  
theano函数官方文档：  
[http://deeplearning.net/software/theano/library/tensor/basic.html][http_deeplearning.net_software_theano_library_tensor_basic.html]  
简单易懂：  
http://www.cnblogs.com/YiXiaoZhou/p/6079428.html  
keras官方文档：http://keras-cn.readthedocs.io/en/latest/

## 6.python基础 ##

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

## 7.lua ##

lua面向对象编程，写的很透彻：  
http://www.jellythink.com/archives/529  
.与：区别：  
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 ##

卷积层源码：http://blog.csdn.net/shenxiaolu1984/article/details/52373174  
tensor操作：http://blog.csdn.net/whgyxy/article/details/52204206  
60分钟学torch：  
原版：https://github.com/soumith/cvpr2015/blob/master/Deep%20Learning%20with%20Torch.ipynb  
翻译：http://blog.csdn.net/baidu\_17806763/article/details/61630538  
torch学习资料：http://blog.csdn.net/victoriaw/article/details/71703568  
torch学习系列（1），包含tensor操作：http://blog.csdn.net/whgyxy/article/category/6352333  
torch学习系列（2）http://blog.csdn.net/u010946556/article/category/6216156  
torch.nn模块学习（还有tensorflow、matlab、softmax问题）：http://blog.csdn.net/hejunqing14/article/category/6356970  
torch学习系列（3）：http://blog.csdn.net/Hungryof/article/category/6245605  
torch、自己建立一个层（如xnor）：https://zhuanlan.zhihu.com/p/21550685  
官方：http://torch.ch/docs/developer-docs.html  
一些torch小函数：http://blog.csdn.net/JIEJINQUANIL/article/category/5884857  
关于torch建立层汇总：  
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与Keras（Keras中文官方文档）：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  
将tensorflow移植到android手机实现物体识别！！[http://blog.csdn.net/xiaopihaierletian/article/details/61933695][http_blog.csdn.net_xiaopihaierletian_article_details_61933695]  
tensorflow-API：http://www.jianshu.com/nb/5517733  
常用函数：http://blog.csdn.net/lenbow/article/details/52152766  
tensorflow基础学习博客：http://blog.csdn.net/u012436149/article/details/53018924  
tensorflow应用较全：http://blog.csdn.net/helei001/article/details/51842531

## 11、faster ##

http://blog.csdn.net/wopawn/article/details/52223282  
[demo.py解析][demo.py]  
论文解析，很好：[http://blog.csdn.net/wopawn/article/details/52223282\#reply][http_blog.csdn.net_wopawn_article_details_52223282_reply]  
论文翻译，这人有一套rcnn博客：[http://blog.csdn.net/u011534057/article/details/51259812][http_blog.csdn.net_u011534057_article_details_51259812]  
overfeat：[http://blog.sciencenet.cn/blog-1583812-844178.html][http_blog.sciencenet.cn_blog-1583812-844178.html]  
rpn代码解析：[http://blog.csdn.net/sloanqin/article/details/51545125][http_blog.csdn.net_sloanqin_article_details_51545125]

## 12、安装tcl/tk和Tkinter ##

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

## 13、在阅读Faster-RCNN\_TF代码中观看的博客： ##

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与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文件解析：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注释: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产生的问题：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与ndarray操作与转换：http://blog.csdn.net/wyl1987527/article/details/62458057  
★变量、相关变量初始化、保存：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  
★与模型保存读取（saver）相关的一切操作：http://cv-tricks.com/tensorflow-tutorial/save-restore-tensorflow-models-quick-complete-tutorial/  
翻译：http://blog.163.com/wujiaxing009@126/blog/static/7198839920175671529472/  
其余相关：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与tf.all\_variables:http://blog.csdn.net/uestc\_c2\_403/article/details/72356448  
tf.gradients 与 tf.stop\_gradient() :http://blog.csdn.net/u012436149/article/details/53905797

## 14、haar与adaboost ##

利用OpenCV自带的haar training程序训练分类器 ：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人脸特征检测：http://blog.csdn.net/zmdsjtu/article/details/52422847  
训练常见问题：http://www.cnblogs.com/chensheng-zhou/p/5542887.html

## 15、dlib array2d与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、三维重建 ##

vcglib -github：https://github.com/cnr-isti-vclab/vcglib  
win10+vs+cuda ：http://blog.csdn.net/u011821462/article/details/50145221  
★三维可视化工程：http://redwood-data.org/indoor/tutorial.html  
win10+vs2015 meshlab编译 ：http://blog.csdn.net/hanshuobest/article/details/71525388  
windows-git：http://blog.csdn.net/qq\_34698126/article/details/53521187

## 17、kinfu环境配置 ##

kinfu安装配置全解：http://blog.csdn.net/alan\_1550587588/article/details/54582192  
VS2010和IVF2011的安装教程 Fortran：  
http://wenku.baidu.com/view/9e28de1b01f69e314332949c.html  
Fortran认证书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++笔记：http://www.cnblogs.com/ggjucheng/archive/2012/08/18/2645319.html  
typedef：http://blog.csdn.net/ameyume/article/details/6326278  
指针的指针：http://blog.jobbole.com/60647/  
成员函数指针：http://blog.csdn.net/jinjinclouded/article/details/5189540  
c++指针：http://www.cnblogs.com/ggjucheng/archive/2011/12/13/2286391.html  
qt学习：http://www.kuqin.com/qtdocument/tutorial.html  
argc和argv含义及用法 ：http://blog.csdn.net/dcrmg/article/details/51987413  
虚函数与纯虚函数：http://blog.csdn.net/xwpc702/article/details/8670025  
http://blog.csdn.net/hackbuteer1/article/details/7558868

## 19、ELL ##

安装中出现问题解决（中文）博客：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、光流测速度 ##

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  
加载深度信息求速度原理：  
![这里写图片描述][format_png]  
![这里写图片描述][format_png 1]

## 21、识别走过的弯路： ##

【人体姿态】Stacked Hourglass算法详解 （torch代码）：http://blog.csdn.net/shenxiaolu1984/article/details/51428392  
Object Detection︱RCNN、faster-RCNN框架的浅读与延伸内容笔记 ：  
http://blog.csdn.net/roslei/article/details/73459873  
ipython-notebook caffe识别与可视化：http://nbviewer.jupyter.org/github/BVLC/caffe/blob/master/examples/00-classification.ipynb\#Classification:-Instant-Recognition-with-Caffe

## 22、语义分割与识别 ##

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与SqueezeNet ##

SqueezeNet-github:https://github.com/DeepScale/SqueezeNet  
Deep Compression阅读理解及Caffe源码修改 ：http://blog.csdn.net/may0324/article/details/52935869  
阅读理解：  
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  
压缩caffemodel：https://github.com/RalphMao/demo\_nn\_compress  
SqueezeNet+Faster-RCNN+OHEM：http://blog.csdn.net/u011956147/article/details/53714616

## 24、TFFRCNN（基于Faster-RCNN\_TF修改） ##

https://github.com/CharlesShang/TFFRCNN，内含PVANET模型  
运行TFFRCNN：http://blog.csdn.net/yuexin2/article/details/75019330  
TFRRCNN训练自己的模型：http://blog.csdn.net/yuexin2/article/details/75025720

## 25、嵌入式网络 ##

CNN 模型压缩与加速算法综述 :http://blog.csdn.net/QcloudCommunity/article/details/77719498  
YOLO对比SVM+HOG 耗时更短 处理更精确（附github资源）：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  
//（有实现链接）http://blog.csdn.net/mao\_feng/article/details/75116085  
//论文翻译：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.卷积加速相关 ##

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.强化学习 ##

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相关工程与讨论 ##

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  
☆修改梯度相关 http://blog.csdn.net/buyi\_shizi/article/details/51512848  
http://blog.csdn.net/yihaizhiyan/article/details/44159063

## 32、FCN训练自己的数据集 ##

详细版本：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、服务器搭建 ##

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、推荐系统 ##

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

讲解：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  
添加新层：  
https://blog.csdn.net/shuzfan/article/details/51322976（cutoff）  
https://blog.csdn.net/wfei101/article/details/76735760（盗版）  
https://blog.csdn.net/kuaitoukid/article/details/41865803（maxout与NIN）  
https://blog.csdn.net/xizero00/article/details/52529341（图像缩放）  
https://blog.csdn.net/happyflyy/article/details/54866037（maxout）  
caffe函数解析：  
https://blog.csdn.net/seven\_first/article/details/47378697

caffe卷积实现原理：  
https://blog.csdn.net/jiongnima/article/details/69055941  
im2col原理：  
https://blog.csdn.net/jiongnima/article/details/69736844

## 36、TernausNet ##

https://github.com/ternaus/TernausNet  
https://github.com/ternaus/robot-surgery-segmentation

## 37、caffe添加新层与实现原理 ##

很多篇都有用：https://blog.csdn.net/tangwei2014?viewmode=contents  
添层（facenet）：https://blog.csdn.net/langb2014/article/details/50489305  
https://blog.csdn.net/seven\_first/article/details/50272005  
caffe源码解析：https://blog.csdn.net/seven\_first/article/category/5721883

## 38、人脸画像 ##

https://github.com/BoyuanJiang/Age-Gender-Estimate-TF

## 39、tensorflow-model2caffemodel ##

https://blog.csdn.net/jiongnima/article/category/7245212

## 40、聊天机器人汇总 ##

https://github.com/fateleak/awesome-chatbot-list

## 41、SGM-NET: ##

github:  
https://github.com/dhernandez0/sgm  
https://github.com/fixstars/libSGM  
https://github.com/WanchaoYao/SGM  
博客：  
https://blog.csdn.net/zilanpotou182/article/details/73382412  
https://blog.csdn.net/wsj998689aa/article/details/49464017  
https://www.cnblogs.com/hrlnw/p/4746170.html  
https://blog.csdn.net/qq\_31785865/article/details/78451880  
https://blog.csdn.net/laobai1015/article/details/52527233  
http://lib.csdn.net/article/datastructure/10208

## 42、caffe矩阵操作 ##

cblas\_sgemm：https://blog.csdn.net/ZhikangFu/article/details/78258393  
conv层讲解：https://blog.csdn.net/sinat\_22336563/article/details/69808612  
caffe讲解全（1）：https://blog.csdn.net/seven\_first/article/details/47378697\#1-caffecpugemm-%E5%87%BD%E6%95%B0  
caffe讲解全（2）：https://blog.csdn.net/langb2014/article/details/51558515

caffe讲解全：https://blog.csdn.net/jiongnima/article/category/6436731

## 43、xnor新理解与新工程 ##

pyrorch：https://github.com/jiecaoyu/XNOR-Net-PyTorch/tree/7f84f1bf6921bc99b05bbc869dddf2bd64989a40  
tensorflow：https://github.com/AngusG/tensorflow-xnor-bnn  
问题：https://github.com/jiecaoyu/XNOR-Net-PyTorch/issues/13  
反向传播：https://github.com/jiecaoyu/XNOR-Net-PyTorch/blob/master/notes/notes.pdf

## 44、多线程 ##

boost::thread  
https://www.jianshu.com/p/0b2e360243f4  
https://www.jianshu.com/p/30e79d2a8f7d  
https://blog.csdn.net/zhuxiaoyang2000/article/details/6588031/

pthread  
http://www.runoob.com/cplusplus/cpp-multithreading.html  
https://blog.csdn.net/hudashi/article/details/7709413  
http://www.docin.com/p-65547314.html  
https://www.ibm.com/developerworks/cn/linux/l-pthred/index.html  
http://www.cppblog.com/saha/articles/189802.html

## 45、NEON ##

https://download.csdn.net/download/jieweijason/10200330  
https://developer.arm.com/technologies/neon/intrinsics  
https://blog.csdn.net/may0324/article/details/72847800  
https://www.jianshu.com/p/68879baa7c1f?from=timeline&isappinstalled=0

https://www.cnblogs.com/hrlnw/p/3767853.html  
https://www.cnblogs.com/hrlnw/p/3723072.html

## 46、MobileNet ##

prototxt：  
https://github.com/suzhenghang/MobileNetv2/tree/master/.gitignore  
https://github.com/austingg/MobileNet-v2-caffe  
mobilenet-sdd：  
https://github.com/PINTO0309/MobileNet-SSD  
https://github.com/PINTO0309/MobileNet-SSDLite-RealSense-TF

## 47、MobileNet/shuffleNet with YOLO/SSD ##

https://github.com/eric612/MobileNet-YOLO  
https://github.com/PINTO0309/MobileNet-SSD  
https://github.com/chuanqi305/MobileNet-SSD  
https://github.com/chuanqi305/MobileNetv2-SSDLite  
https://github.com/FreeApe/VGG-or-MobileNet-SSD  
https://github.com/farmingyard/ShuffleNet  
https://github.com/linchaozhang/shufflenet-ssd

https://github.com/chuanqi305/SqueezeNet-SSD  
https://github.com/ChenYingpeng/caffe-ssd-frameworks

## 48 嵌入式/压缩神经网络相关工作汇总 ##

https://www.ctolib.com/ZhishengWang-Embedded-Neural-Network.html

## 49、Momenta ##

1、多进程：https://blog.csdn.net/zouxy09/article/details/49031845\#commentBox  
2、gamma矫正：https://blog.csdn.net/linqianbi/article/details/78617615  
3、仿射变化：https://blog.csdn.net/wsx\_9999/article/details/80441125

## 50、毕设总结 ##

dw\_conv比conv慢：https://blog.csdn.net/liu1152239/article/details/81478463  
conv bn融合：https://www.cnblogs.com/nowgood/p/juan-ji-ceng-he-liang-hua-ceng-rong-he.html

## 51、anchor初始化计算 ##

https://blog.csdn.net/Pattorio/article/details/80095511  
https://blog.csdn.net/m\_buddy/article/details/82926024  
https://github.com/Jumabek/darknet\_scripts

## 52、shufflenetv2-ssdlite（bdd-trafficlight） ##

dbb转voc  
https://github.com/leeesangwon/bdd100k\_to\_VOC  
https://blog.csdn.net/qq\_17278169/article/details/82189776  
voc转lmdb  
https://blog.csdn.net/jiang\_ming\_/article/details/81068854  
https://blog.csdn.net/LOVExinxinsensen/article/details/80982423  
txt转voc  
https://blog.csdn.net/pursuit\_zhangyu/article/details/79949947  
https://blog.csdn.net/yjl9122/article/details/56842098

## 53、数据增强、samplepairing与mixup ##

https://spaces.ac.cn/archives/5693  
https://www.jianshu.com/p/003c5b6477ba  
https://blog.csdn.net/stezio/article/details/87816785

## 54、lasso回归与维数灾难 ##

https://blog.csdn.net/xiaozhu\_1024/article/details/80585151  
https://www.linuxidc.com/Linux/2016-01/127857.htm

## 55、 ##

centernet pytorch1.0+版本问题：  
https://www.gitmemory.com/issue/xingyizhou/CenterNet/7/486653333

[http_colah.github.io_posts_2015-08-Understanding-LSTMs]: http://colah.github.io/posts/2015-08-Understanding-LSTMs/
[http_www.jianshu.com_p_9dc9f41f0b29]: http://www.jianshu.com/p/9dc9f41f0b29
[http_karpathy.github.io_2015_05_21_rnn-effectiveness]: http://karpathy.github.io/2015/05/21/rnn-effectiveness/
[http_blog.csdn.net_heyongluoyao8_article_details_48636251]: http://blog.csdn.net/heyongluoyao8/article/details/48636251
[http_cs.stanford.edu_people_karpathy_deepimagesent]: http://cs.stanford.edu/people/karpathy/deepimagesent/
[https_github.com_karpathy_neuraltalk]: https://github.com/karpathy/neuraltalk
[http_lib.csdn.net_article_deeplearning_57863_knId_1726]: http://lib.csdn.net/article/deeplearning/57863?knId=1726
[http_blog.csdn.net_samylee_article_details_53414108]: http://blog.csdn.net/samylee/article/details/53414108
[http_blog.csdn.net_sinat_30071459_article_details_53100791]: http://blog.csdn.net/sinat_30071459/article/details/53100791
[http_blog.csdn.net_u014595019_article_details_52571966]: http://blog.csdn.net/u014595019/article/details/52571966
[http_blog.csdn.net_xbinworld_article_details_44464663]: http://blog.csdn.net/xbinworld/article/details/44464663
[http_blog.csdn.net_hjimce_article_details_49255013]: http://blog.csdn.net/hjimce/article/details/49255013
[https_www.zybuluo.com_hanbingtao_note_433855]: https://www.zybuluo.com/hanbingtao/note/433855
[http_www.deeplearning.net_tutorial]: http://www.deeplearning.net/tutorial/
[http_deeplearning.net_software_theano_library_tensor_basic.html]: http://deeplearning.net/software/theano/library/tensor/basic.html
[http_blog.csdn.net_xiaopihaierletian_article_details_61933695]: http://blog.csdn.net/xiaopihaierletian/article/details/61933695
[demo.py]: http://blog.csdn.net/xzzppp/article/details/52073107
[http_blog.csdn.net_wopawn_article_details_52223282_reply]: http://blog.csdn.net/wopawn/article/details/52223282#reply
[http_blog.csdn.net_u011534057_article_details_51259812]: http://blog.csdn.net/u011534057/article/details/51259812
[http_blog.sciencenet.cn_blog-1583812-844178.html]: http://blog.sciencenet.cn/blog-1583812-844178.html
[http_blog.csdn.net_sloanqin_article_details_51545125]: http://blog.csdn.net/sloanqin/article/details/51545125
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