Jacobian矩阵和Hessian矩阵:http://jacoxu.com/jacobian%E7%9F%A9%E9%98%B5%E5%92%8Chessian%E7%9F%A9%E9%98%B5/
从传统检测方法到深度神经网络框架:http://www.sohu.com/a/131923395_465975
三种强大的物体识别算法:https://blog.csdn.net/liuqz2009/article/details/47623647
三大物体识别算法--SIFT/SURF、haar特征、广义hough变换的特性深入剖析:https://blog.csdn.net/zj360202/article/details/41518319
主成分分析(PCA)原理详解:https://blog.csdn.net/zhongkelee/article/details/44064401
https://blog.csdn.net/augster/article/details/53066675
基于图像形状的一种比较漂亮的分类算法Hausdorff Distance:https://blog.csdn.net/lishuhuakai/article/details/53573241
如何通俗易懂地解释「协方差」与「相关系数」的概念?:https://www.zhihu.com/question/20852004
协方差的意义和计算公式:https://blog.csdn.net/yangdashi888/article/details/52397990
为什么样本方差(sample variance)的分母是 n-1?:https://www.zhihu.com/question/20099757
方差,协方差、标准差,与其意义:https://blog.csdn.net/yangdashi888/article/details/52397990
协方差的特征值和特征向量:https://blog.csdn.net/u010182633/article/details/45921929
理解SVM(一)——入门SVM和代码实现:http://lib.csdn.net/article/machinelearning/34998
玩儿懂深度学习Part 6:物体的识别与定位:http://ju.outofmemory.cn/entry/330832
基于边界的模板匹配的原理及算法实现:https://blog.csdn.net/huixingshao/article/details/45560643
Andreas Hofhauser:http://campar.in.tum.de/Main/AndreasHofhauser
Sift中尺度空间、高斯金字塔、差分金字塔(DOG金字塔)、图像金字塔:https://blog.csdn.net/dcrmg/article/details/52561656
SIFT特征提取分析:https://blog.csdn.net/abcjennifer/article/details/7639681/
用Python和OpenCV创建一个图片搜索引擎的完整指南:
http://python.jobbole.com/80860/
https://blog.csdn.net/coderhuhy/article/details/46575667
图像检索(CBIR)三剑客之BoF、VLAD、FV:https://blog.csdn.net/garfielder007/article/details/50440979
指纹识别算法:http://www.dewen.net.cn/q/757
https://zm8.sm-tc.cn/?src=l4uLj8XQ0IiIiNGMl56NmpWM0ZyQktCckJuajNCcj4%2FQx8%2FOzQ%3D%3D&uid=91e12bcf7b8b965866e6bd2a9bd4bca7&hid=98ccbda5975cd189db0993e05e25eff4&pos=4&cid=9&time=1526948519149&from=click&restype=1&pagetype=0000004000000402&bu=web&query=%E5%9B%BE%E7%89%87%E5%AF%B9%E6%AF%94%E7%AE%97%E6%B3%95&mode=&v=1&province=%E5%8C%97%E4%BA%AC%E5%B8%82&city=%E5%8C%97%E4%BA%AC%E5%B8%82&uc_param_str=dnntnwvepffrgibijbprsvdsdichei
(好文)做图像识别和检测的相关工作,有C++基础,OpenCV较熟,想找些基础项目实战练一下手有什么推荐吗?:https://www.zhihu.com/question/276925640/answer/390020683?utm_source=qq&utm_medium=social&utm_oi=851579121388646400
如何自己搭建一个 QQ 机器人?:https://www.zhihu.com/question/19906665
https://www.jianshu.com/p/9e18b46bfc65
python3+dlib实现人脸识别和情绪分析:http://www.php.cn/python-tutorials-393748.html
PCA主成分分析文章
PCA(主成分分析)python实现:https://www.jianshu.com/p/4528aaa6dc48
利用K-NN通过PCA进行图片分类:https://blog.csdn.net/u014432647/article/details/77771700
图像特征提取之--PCA方法:https://blog.csdn.net/lifeng_math/article/details/50014073
PCA主成分分析Python实现:https://www.cnblogs.com/clnchanpin/p/7199713.html
基于KNN模型的分类算法研究:https://www.cnblogs.com/baiboy/p/pybnc2.html#
图像特征提取三大法宝:HOG特征,LBP特征,Haar特征:http://dataunion.org/20584.html
c++截图:http://www.cppblog.com/weiym/archive/2014/09/22/208379.html
车道线检测:https://zhuanlan.zhihu.com/p/35134563
TensorFlow学习笔记:Retrain Inception_v3(一):https://www.jianshu.com/p/613c3b08faea
tensorflow实现 Inception V3:https://blog.csdn.net/ifruoxi/article/details/78311595
inceptionV3迁移学习并保存完整的pb文件: https://blog.csdn.net/hust_bochu_xuchao/article/details/79657154
【OpenCV_contri】找出任意物体可能在的位置(Selective search,物体检测):https://blog.csdn.net/zmdsjtu/article/details/78242521
Selective Search for Object Recognition解读:https://blog.csdn.net/mao_kun/article/details/50576003
【opencv】目标识别——轮廓匹配:https://blog.csdn.net/qq_15947787/article/details/72773893?ABstrategy=codes_snippets_optimize_v3
Tensorflow实现卷积神经网络,用于人脸关键点识别:https://blog.csdn.net/thriving_fcl/article/details/50909109
车牌识别“:https://github.com/zeusees
深度学习图像识别、分类、人脸识别:http://www.gudanba.com/613.html ****
----------语义分割专栏-----------------------
【Keras】基于SegNet和U-Net的遥感图像语义分割、;https://cloud.tencent.com/developer/article/1099793
主要语义分割网络:FCN,SegNet,U-Net以及一些半监督方法:http://www.elecfans.com/d/688859.html
语义分割(semantic segmentation) 常用神经网络介绍对比-FCN SegNet U-net DeconvNet:https://blog.csdn.net/zhyj3038/article/details/71195262(解释的更加详细,清楚)
利用Tensorflow实现语义分割全卷积网络:https://www.sohu.com/a/130675960_642762
TFRecord 的使用:https://blog.csdn.net/xueyingxue001/article/details/68943650
图像分割semantic segmentation SegNet详解+tensorflow代码使用【附下载】:https://blog.csdn.net/k87974/article/details/79926014 https://blog.csdn.net/lwgechen/article/details/78275924
SegNet-论文笔记-理解-卷积神经网络CNN(4)—— SegNet:https://blog.csdn.net/tuzixini/article/details/78760158 https://blog.csdn.net/fate_fjh/article/details/53467948 http://mi.eng.cam.ac.uk/projects/segnet/tutorial.html
学习TensorFlow,调用预训练好的网络(Alex, VGG, ResNet etc):https://blog.csdn.net/helei001/article/details/53159690
利用TensorFlow实现VGG16:https://blog.csdn.net/v1_vivian/article/details/77898652
Tensorflow加载预训练模型和保存模型:https://blog.csdn.net/huachao1001/article/details/78501928
TensorFlow的python代码练习:https://segmentfault.com/a/1190000011212793