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793r
- 版主要修改了以下地方： 1、修改了网站风格，过年了嘛 2、增加班级排行功能,调动用户进入班级的积极性 3、去掉新闻功能,此栏目实在是多余的,一点用也没有 4、学校/班级明星改为10个名额,改为第一名头像显示,其余文字显示 5、修正班级相册和投票的一些错误,还有其它小错误也进行了修复 6、论坛增加了移帖功能 7、论坛增加了多版主功能-revised version of the following main areas : 1, which amended the we
src
- Real-time line detection through an improved Hough transform voting scheme 的matlab实现-Implement of Real-time line detection through an improved Hough transform voting scheme
Tensor-Voting
- 张量投票算法,对连接断裂的线段有很好的效果-Tensor Voting
ShapeContextProjects
- 图形识别算法 可用于图形识别以及 验证码识别研究-The main part of the code uses improved Shape Context as feature descr iptor and fit into a Hough Voting framework to detect objects. It can be used for initial hypothesis proposal. I hope you find this code helpful!
Segmentation
- 这个方法有两个好处。 （ a ）虽然只是一个半径差逼近，很容易找到最高在一个小蓄电池，因为通过降低 隐平滑做的蓄电池。（ b ）在同一时间处理时间搜索减少 -Pattern Recognition and Image Procesing Group. The size of the accumulator is varied as hierarchical voting is performed. This has two advantages. [a] While the
biye
- 基于投票算法的目标跟踪,基于二阶非线性投票的多目标跟踪算法。该算法通过目标匹配得到同一目标在不同帧中的位置，同时利用特征监测来处理目标的遮挡、分裂问题，并实现目标特征的实时更新。在目标匹配过程中，通过对目标前一帧与当前帧的特征相似性进行投票，得到匹配目标。利用视频图像进行实验，结果表明：该方法对噪声、阴影、遮挡、分裂等具有良好的鲁棒性，较好地实现了多目标的跟踪。-The method used object matching to get objects’ position in differe
HOUGH_METHOD_LOCATICATION
- 使用HOUGH变换的方法进行虹膜定位，比传统道哥曼投票的方法具有更快的速度-HOUGH Transform method using the iris position,faster than the traditional voting method Gorman Road
Voting-strategy
- 本文提出了一种由粗到细的图像配准方法。该方法首先由多尺度Harris角点检测 算法提取出参考图像和目标图像的特征角点-This paper presents a coarse-to-fine image registration methods. In this method, the multi-scale Harris corner detection algorithm to extract the reference image and the target image featur
Rank-Fusion-Algorithms
- 该文分析了基于投票模型的排序合成问题。在讨论2个常用的投票规则Borda 和Condorcet的基础上，介绍了用图论算法实现的淘汰投票算法，包括Kemeny算法-This paper analyzes the voting model based on sorting synthesis problem. In discussing two common Borda and Condorcet voting rules based on graph theory presented algo
5
- 本文提出了一种基于特征点的全自动无缝图像拼接方法。该方法采用对于尺度具有鲁棒性的SIFT 算法进行特征点的提取与匹配，并通过引导互匹配及投票过滤的方法提高特征点的匹配精确度，使用稳健的RANSAC 算法求出图像间变换矩阵H 的初值并使用LM 非线性迭代算法精炼H，最终使用加权平滑算法完成了图像的无缝拼接。整个处理过程完全自动地实现了对一组图像的无缝拼接，克服了传统图像拼接方法在尺度和光照变化条件下的局限性。实验结果验证了方法的有效性。-This paper presents a feature
PiPei
- 基于VC++6.0开发环境，用OpenCv编程，实现基于投票策略的角点匹配算法！-VC++6.0 based development environment, with OpenCv programming, policy-based voting corner matching algorithm!
image-search-based-on-contour
- 这是我的毕业设计，基于轮廓的图像搜索，环境opencv2.1 vs2008，先配置好，才能运行这个程序，主要算法霍夫投票机制，搜全率和准确率还不错，欢迎下载。-This is my graduation project, profile-based image search, environmental opencv2.1 vs2008, be configured to run this program, the main operator Fahuo Fu voting mechanism,
science
- Real-time line detection through an improved Hough transform voting scheme
Ferrari
- We present an object class detection approach which fully integrates the complementary strengths offered by shape matchers. Like an object detector, it can learn class models directly from images, and can localize novel instances in the prese
stereo_sad
- 自己编写的立体匹配源代码，采用SAD作为费用累积函数，并且加入了L-R Check和邻域投票法解决误匹配问题-Stereo matching source code to write your own, using the SAD as cost cumulative function, and LR Check and neighborhood voting method to solve the problem of mismatching
Voting
- 应用于图像分类编码中硬投票与软投票两种算法的实现与比较-Implementation and comparison of hard to vote with soft voting two algorithms applied to image classification and coding
HL
- Hough line 是一個用於圖像分析的特徵提取技術，計算機視覺，數字圖像處理該技術的目的是不完善的情況下，在一定的對象一類形狀的投票程序。-The Hough transform is a feature extraction technique used in image analysis, computer vision, and digital image processing. The purpose of the technique is to find imperfect ins
Recog_Test_Vote
- face recognition test by voting
tensor-voting
- 张量投票他的项目包含有表决权框架作为实施 组类，工程toghether作为一个“机制”-his project contains the implementation of the voting framework as a set of classes that works toghether as a "mechanism" (see "Doing hard Time") to give principally 4 use cases
CUDA-CNN-master
- CNN cuda的加速。 start-of-art结果的流行的数据集 1。测试mnist并获得99.76 ,投票后(99.82 )(最好的99.79 ) 2。测试cifar-10并获得81.42 最好(90 ) 3。测试cifar - 100和51.13 (最好的65 )-CNN accelerated by cuda. The start-of-art result s of popular datasets 1. Test on mnist and get 99.76