搜索资源列表
Paper]
- 最新顶级会议CVPR2011关于人体姿态识别文章-Paper] Real-time Human Pose Recognition in Parts from Single Depth Images 2011CVPRBodyPartRecognition
adaboost
- Adaboost 算法的源程序，可以帮助我们深入学习 adaboost 算法-Adaboost algorithm source code, to help our in-depth learning algorithm adaboost
123
- 比较全面的指纹识别文件,全面深入的介绍指纹识别相关领域的技术开发过程-Fingerprint of a more comprehensive document, comprehensive and in-depth introduction to the field of fingerprint recognition technology related to the development process
mips16_functions_c32_example
- This article covers the so-called "min-cost flow" problem, which has many applications for both TopCoder competitors and professional programmers. The article is targeted to readers who are not familiar with the subject, with a focus more on providin
img-mhrg
- 分类器设计的好坏对于图像识别效果有着重要影响. 本文基于黄等所提出的识别方法,定义了一类更 广泛的隶属函数,并借助于投影算子理论、子空间理论,对所提隶属函数的性质进行了深入的理论分析,证明了所提隶 属函数所具有的若干良好特性,-Classifier design is good or bad for the image recognition results have an important impact. Yellow, etc. Based on the proposed reco
demo
- 车辆牌照简易识别系统.初步开发,未深入进行,可以进行下一步开发-Simple vehicle license identification system. Initial development, no depth, can be further developed
face
- 图像识别系统的结构与工作原理，在对图像预处理、特征提取、分类、图像匹配算法进行深入研究和分 析的基础上，分析和比较了各种算法的优缺点-Image Recognition System structure and working principle, in the image preprocessing, feature extraction, classification, image matching algorithm in-depth research and analysis, ba
gesture-recognition
- 基于kinect获取深度图像来进行手势识别-Based on depth images for kinect for gesture recognition
moshishibiekejian
- 里面含有丰富的模式识别相关知识，入门和深入都很有好处，985大学的标准课件-Which is rich in pattern recognition, knowledge, very good entry and in-depth, 985 University of standard courseware
KinectUserHeight
- 利用Kinect的深度信息，测量出人得身高。-Take advantage of the the Kinect depth of information, measuring out the man was tall.
CDBM-master
- 深度学习理论下的深度波尔兹曼机（DBM），用于图像的自动的特征提取及识别。-Depth Depth Boltzmann machine learning theory under (DBM), for automated image feature extraction and recognition.
Release
- 闲时无聊，搭了一个基于深度神经网络的手写数字识别系统。该系统在手写数字数据库mnist测试达到了99.22 的准确率。整个系统基于C++开发，可以很方便的移植到其他平台。 其中手写数字数据库mnist（http://yann.lecun.com/exdb/mnist/），有60000个训练样本数据集和10000个测试用例。它是由Google实验室的Corinna Cortes和纽约大学柯朗研究所的Yann LeCun建立的一个手写数字数据库。同时它是nist数据库的一个子集。
DeepLearnToolbox-master
- 这是关于深度学习的一些很重要的代码 包括基础的深度学习 RBM等，还有用深度学习去训练神经网络-This is about the depth of learning, including some very important code based on the depth of learning RBM, as well as by the depth of learning to train the neural network, etc.
CNNdaima-tuxiangshibie
- 深度学习中的CNN方法，层数由原先的五层增加到七层，使用最新的RELU激活函数代替原先的sigm函数，能运行-CNN depth learning method, the number of layers the original five to seven, with the latest RELU activation function replaces sigm function, you can run it
DMM_HOG
- 行为识别利用深度图提取特征识别。DMM方法(Behavior recognition using depth map to extract feature recognition)