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[OpenCV] opencv2.1reference_manual

Description: opencv 2.1 使用手册兼容以前C使用方式 opencv2.0后，新的c++ python接口描述-opencv 2.1 reference manual
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[OpenCV] opencvReferenceManual(2.0-2.1)

Description: 这是opencv2.0和2.1的完整参考手册（英文），还提供了emgu.cv2.0的部分使用手册，可以弥补opencv没有介绍的库函数。-This is a complete opencv2.0 and 2.1 Reference Manual (English), also provides emgu.cv2.0 part of the manual, you can not make up for opencv library functions described.
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[Special Effects] OpenCV2.2_API_Specification

Description: 本文档包括了OpenCV2.2版（2010年12月推出，目前最新版）中所有API函数的说明，包括C、C++、Python中调用OpenCV的所有接口函数，是大家开发计算机视觉、图像处理、模式识别程序的好参考。OpenCV2.2提供了支持Visual Studio 2010的可执行版本，并且添加了HOG行人检测器，真是不可多得的好东西。-This document includes OpenCV2.2 edition (December 2010 launch, the latest version) a description of all API functions, including C, C++, Python OpenCV call all the interface functions, there is little development of computer vision, image processing, pattern a good reference for identification procedures. OpenCV2.2 supported executable version of Visual Studio 2010 and added the HOG pedestrian detector is really a rare good thing.
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[Graph Recognize] face-recognatiojn

Description: 这是一个人脸识别的小程序供大家参考采用C++结合OPENCV-This is a recognition of the small program for your reference
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[matlab] DeepLearnToolbox_CNN_lzbV2.0

Description: DeepLearnToolbox_CNN_lzbV2.0 深度学习,卷积神经网络,Matlab工具箱参考文献: [1] Notes on Convolutional Neural Networks. Jake Bouvrie. 2006 [2] Gradient-Based Learning Applied to Document Recognition. Yann LeCun. 1998 [3] https://github.com/rasmusbergpalm/DeepLearnToolbox 作者：陆振波电子邮件：luzhenbo2@qq.com 个人博客: http://blog.sina.com.cn/luzhenbo2 毕业院校：海军工程大学，船舶与海洋工程(水声工程)，博士精通方向：数据挖掘，数字信号(图像、视频)处理，人工智能与模式识别，群体智能优化，非线性与混沌，支持向量机，Matlab与VC++混编擅长技能：战略规划，团队管理，C，C++，Matlab，OpenCV，DSP，并行计算，图像处理，模式识别，机器学习，智能视觉，神经网络，人脸检测，行人检测，车牌识别，机器视觉，特征提取，支持向量机，无人驾驶，自动驾驶，智能眼镜，辅助驾驶，ADAS，AdaBoost，LBP，HOG，MeanShift，目标检测，目标识别，目标跟踪，数据挖掘，大数据 -DeepLearnToolbox CNN lzbV2.0 Deep Learning, convolution neural network, Matlab toolbox reference: [1] Notes on Convolutional Neural Networks. Jake Bouvrie. 2006 [2] Gradient-Based Learning Applied to Document Recognition. Yann LeCun. 1998 [3] https://github.com/rasmusbergpalm/DeepLearnToolbox Author: Lu Zhenbo E-mail: luzhenbo2@qq.com Personal blog: http://blog.sina.com.cn/luzhenbo2 Graduated: Naval University of Engineering, Naval Architecture and Marine Engineering (Underwater Acoustic), Dr. Proficient direction: data mining, digital signal (image, video) processing, artificial intelligence and pattern recognition, swarm intelligence optimization, nonlinear and chaotic, support vector machines, Matlab and VC++ mixed Good skills: strategic planning, team management, C, C++, Matlab, OpenCV, DSP, parallel computing, image processing, pattern recognition, machine learning, intelligent vision, neural networks, face detection, pedestrian detection, lice
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[AI-NN-PR] DeepLearnToolbox_CNN_lzbV3.0

Description: CNN - 主程序参考文献: [1] Notes on Convolutional Neural Networks. Jake Bouvrie. 2006 [2] Gradient-Based Learning Applied to Document Recognition. Yann LeCun. 1998 [3] https://github.com/rasmusbergpalm/DeepLearnToolbox 作者：陆振波电子邮件：luzhenbo2@qq.com 个人博客: http://blog.sina.com.cn/luzhenbo2 毕业院校：海军工程大学，船舶与海洋工程(水声工程)，博士精通方向：信号处理，图像处理，人工智能，模式识别，支持向量机，深度学习，机器学习，机器视觉，群体智能，Matlab与VC++混编擅长技能：战略规划，团队管理，C，C++，Matlab，OpenCV，DSP，并行计算，图像处理，智能视觉，卷积神经网络，人脸检测，行人检测，车牌识别，特征提取，智能眼镜，辅助驾驶，ADAS，AdaBoost，LBP，HOG，MeanShift，目标检测，目标识别，目标跟踪，大数据 - CNN- the main program reference: [1] Notes on Convolutional Neural Networks. Jake Bouvrie. 2006 [2] Gradient-Based Learning Applied to Document Recognition. Yann LeCun. 1998 [3] https://github.com/rasmusbergpalm/DeepLearnToolbox Author: Lu Zhenbo E-mail: luzhenbo2@qq.com Personal blog: http://blog.sina.com.cn/luzhenbo2 Graduated: Naval University of Engineering, Naval Architecture and Marine Engineering (Underwater Acoustic), Dr. Proficient direction: signal processing, image processing, artificial intelligence, pattern recognition, support vector machines, deep learning, machine learning, machine vision, swarm intelligence, Matlab and VC++ mixed Good skills: strategic planning, team management, C, C++, Matlab, OpenCV, DSP, parallel computing, image processing, intelligent vision, convolution neural network, face detection, pedestrian detection, license plate recognition, feature extraction, smart glasses, driver assistance, ADAS, AdaBoost, LBP, H
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