搜索资源列表
maxminestimate
- 最大最小值估计，适合学习统计理论和模糊方面的结合应用，尤其是在模式识别方面的分类。-largest minimum estimate for statistical learning theory and fuzzy combination of the application, especially in regard to the classification of pattern recognition.
Class-separability
- 类可分离性的判别，特征选择与特征提取的任务是求出一组对分类最有效的特征因此需要有定量分析比较的方法，判断所得到的特征维数及所使用特征是否对分类最有利，这种用以定量检验分类性能的准则称为类可分离性判据。 类别可分离性判据，用来检验不同的特征组合对分类性能好坏的影响，并用来导出特征选择与特征提取的方法。 理想准则：某组特征使分类器错误概率最小-Class separability of discrimination, feature selection and feature extract
pr_zuidazuixiao
- 模式识别，聚类分析的最大最小距离算法算法Matlab演示-Pattern recognition, cluster analysis algorithm for the maximum minimum distance algorithm Matlab demo
neatestface
- 人脸识别matlab程序，pca主成分分析法，采用最小距离决策-Face recognition matlab program, pca principal component analysis method, using a minimum distance between the decision-making
1
- Cognitive radio frequency spectrum detection-The spectrum sensing of a wideband frequency range is studied by dividing it into multiple subbands. It is assumed that in each subband either a primary user (PU) is active or absent in a additive white
BinarizationAlgorithm
- 用matlab实现的otsu全局二值化算法、kittler 最小分类错误(minimum error thresholding)全局二值化算法、niblack局部二值化算法-Using matlab implementation otsu global binarization algorithm, kittler minimum classification error (minimum error thresholding) the global binarization algorithm
oushijulifu
- 现代模式识别根据相似阈值和最小距离原则的简单聚类方法-Modern pattern recognition based on the similarity threshold values and the principles of a simple minimum distance clustering method
PR_SimpleClusteringP26
- 孙即祥：《现代模式识别》P.26：根据相似性阈值和最小距离原则的简单聚类方法MATLAB（另一种方法实现同一种算法）-SUN Xiang: " Modern pattern recognition" P.26: According to the similarity threshold and minimum distance principle of a simple clustering method MATLAB (another way to achieve the s
Bayes
- 最小错误概率的Bayes分类器 手写数字识别-Minimum error probability of Bayes classifier handwritten numeral recognition
osjl
- 基于最小欧式距离的模式识别分类，对于简单直观明了。-Pattern recognition based on the minimum Euclidean distance classification, for simple and intuitive to understand.
Bayes
- 传统贝叶斯分类器，最小错误率贝叶斯分类器、最小风险贝叶斯分类器-Traditional Bayesian classifier, the minimum error rate classifier, minimum risk Bayes classifier
Cell_Recognization
- 本系统具有实现细胞识别等相关功能，主要有以下功能：通过阈值设定进行图像的直方图显示，手动选取或手动去除干扰点，图像平滑，还有一些简单的图处理的功能，如腐蚀、膨胀、边缘的提取或区域提取的显示，最后还可以统计出图像中细胞的个数，以及识别出最大最小的细胞。直接运行就可以，功能一目了然。-The system has achieved recognition and other related cellular functions, mainly in the following features: t
Pattern-Recognition-LRB
- 用最邻近模板匹配法，最小错误概率的Bayes方法和Fisher算法分别对数字进行识别-Template matching with the nearest neighbor, minimum error probability of Bayes method and Fisher algorithm to identify each of the figures
money
- traversing a graph and find the minimum of it
numberbie
- 本程序实现了手写数字体的识别，识别算法采用最小欧氏距离法-Realized by the number of fonts handwriting recognition, recognition algorithms using the minimum Euclidean distance method
zhedandanmubiao
- 跟踪的参数（单位为秒）为运动跟踪的最大持续时间最大时间增量为0.5s最小时间增量0.05s-Tracking parameters (unit for seconds) for the track maximum sustained time maximum time increment is 0.5 s minimum time increment 0.05 s
unnamed
- 多类数字识别，将图片分为3*3的区域，在9部分中，通过最小距离法识别测试图片，正确率97 -Many kinds of digital identification, pictures will be divided into 3* 3 area, in nine part, through the minimum distance method identification test images, 97 accuracy
NanoTube
- 使用C++编程语言，开发了“单壁碳纳米管手性矢量识别系统”软件。软件处理结果显示:采用最大类间方差法二值化单壁碳纳米管STM图像，能够保留较多单壁碳纳米管的六边形拓扑结构信息；采用本文设计的射线探测加权法能够快速、准确的识别出六边形碳环的中心。-The processing result with the software indicated more topology structure information could be reserved, when maximal variance
SVM-and--Face-Recognition
- 支持向量机及其在人脸识别中的应用研究 上海交通大学博士论文，在知网上面付费下载得到的。本文从应用的角度出发，较为全面地对一些相关问题进行探讨，并使用Visual C++实现了一个基于支持向量机的人脸识别软件—idTeller。 论文的主要工作和创新点包括： ·提出了两种基于VC边界的支持向量机参数选择算法—固定C算法和VC-CV算法。VC边界是两类支持向量机参数选择的一个理想准则，但它的一些固有缺点使其应用变得困难。本文通过将VC边界转化为VC指标，最终把问题归结为对最小包围体的求解，从理论
minimum-bounding-rectangle-of--mulitiobject___by-
- in object detection mission, we usually need to bound the object with rectangle, which is called minimum bounding rectangle(MBR). My code can bound objects in the .bmp image with MBRs in any direction and Draw them.