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【Special Effects】 SIFT_VC DL : 0: 实现著名的图像特征检测sift算法进行图像的匹配，对于计算机视觉领域的朋友有帮助-Realize well-known image feature detection algorithm sift image matching, computer vision for the field of friends to help
Update : 2024-04-30 Size : 146432 Publisher : 石雷
【Special Effects】 sift DL : 0: SIFT,I.E. Scale-invariant feature transform
Update : 2024-04-30 Size : 400384 Publisher : 赵杰
【Graph Recognize】 4 DL : 0: 基于灰度投影的人脸特征定位的程序代码-Based on gray-scale projection of the facial feature location code
Update : 2024-04-30 Size : 4096 Publisher :
【Special Effects】 zernike DL : 0: 图形图象处理中的一个非常重要的特征的提取算法,zernike矩-Graphic image processing in a very important feature extraction algorithm, zernike Moment
Update : 2024-04-30 Size : 1024 Publisher : 董华丽
【Special Effects】 Space DL : 0: 利用马尔可夫模型估计的条件概率做为空间特征向量，用于图像检索。-Markov model using the estimated conditional probability space as a feature vector for image retrieval.
Update : 2024-04-30 Size : 1024 Publisher : Owenli
【Special Effects】 Texture DL : 1: 计算四个方向的灰度共生矩阵，将其作为纹理特征，是一种纹理特征提取算法。-Calculation of the four directions of Gray Level Co-occurrence matrix as texture features, is a kind of texture feature extraction algorithm.
Update : 2024-04-30 Size : 1024 Publisher : Owenli
【Special Effects】 klt1.3.3 DL : 0: Kanade-Lucas-Tomasi Feature Tracker,用于实现图像目标跟踪算法。-Kanade-Lucas-Tomasi Feature Tracker, used to realize the image target tracking algorithm.
Update : 2024-04-30 Size : 666624 Publisher : 梁潇
【Speech/Voice recognition/combine】 lpcc DL : 0: 用matlab实现LPCC特征的提取的程序！-Using matlab realize LPCC feature extraction procedure!
Update : 2024-04-30 Size : 1024 Publisher : yue
【Special Effects】 statmoments DL : 0: 出自岗厦雷斯的数字图像处理，用于纹理特征提取的获取数据-From Gangxia juarez digital image processing, feature extraction for texture access to data
Update : 2024-04-30 Size : 1024 Publisher : 肖新华
【Special Effects】 iris_gabor_filter DL : 0: 虹膜识别中的特征提取算法：2D-Gabor滤波器算法，将归一化的虹膜图像由此滤波器滤波，可以得到二进制的特征编码。附图片。-Iris recognition in the feature extraction algorithm: 2D-Gabor filter algorithm, the normalized iris image resulting filter can be obtained characteristics of the binary encoding. Attached picture.
Update : 2024-04-30 Size : 958464 Publisher : galaft
【Special Effects】 LDA DL : 0: 线性判别分析（LDA）是一种较为普遍的用于特征提取的线性分类方法。但是将LDA直接用于人耳识别会遇到维数问题和“小样本”问题。人们经过研究，通过多种途径解决了这两个问题并实现了基于LDA的人耳识别。文章对几种基于LDA的人耳识别方法做了理论上的比较和实验数据的支持，这些方法包括Fisherears、DLDA、VDLDA及VDFLDA。实验结果表明VDFLDA是其中最好的一种方法 -Linear Discriminant Analysis (LDA) is a more common linear feature extraction for classification. LDA but used directly in the human ear to identify problems encountered dimension and the
Update : 2024-04-30 Size : 2129920 Publisher : 冷福
【Graph Recognize】 PCA DL : 0: PCA算法，用于人脸识别的特征提取步骤，是目前最通用的传统的人脸识别算法。通过构建特征子空间进行降维-PCA algorithm for face recognition feature extraction step is currently the most common in traditional face recognition algorithms. By constructing feature subset space dimensionality reduction
Update : 2024-04-30 Size : 1024 Publisher : Jessie
【CSharp】 TextFilter DL : 0: 这是一个利用C#开发的文本过滤的算法，主要包括特征提取，文本表示，和svm的过滤。算法中包括了简单的界面和使用说明。-This is a use of C# Development of text filtering algorithms, including feature extraction, text express, and the SVM filter. Algorithm includes a simple interface and use.
Update : 2024-04-30 Size : 2453504 Publisher : 要尽量
【Other】 FeatureExtractionbyMaximizingtheAverageNeighborhoo DL : 0: 子空间的出现使模式识别有了突破性的发展，而特征提取则是子空间实现的一个重要环节，提取特征的好坏决定了子空间方法的成功与否-The emergence of sub-space to make a breakthrough with the development of pattern recognition, and feature extraction is a sub-space realization of an important link, extract the characteristics of good and bad decisions of the sub-space method of the success of
Update : 2024-04-30 Size : 494592 Publisher : lulu
【Special Effects】 20080213_5e113f3e9a20539660d45C2AGY6dSUCd DL : 0: SIFT算法是一种提取局部特征的算法，在尺度空间寻找极值点，提取位置，尺度，旋转不变量。该程序为sift的演示程序-SIFT algorithm is a local feature extraction algorithms, in scale space to find extreme points, extract the location, scale and rotation invariant. Sift the program for the demo program
Update : 2024-04-30 Size : 1472512 Publisher : 王云云
【Special Effects】 invariant_moment DL : 0: 摘要:提出了一种基于兴趣点不变矩(IPIM)的图像拼接技术。利用Harris 角检测器获取图像中的兴趣点,计算兴趣点邻域的平移、旋转及尺度不变矩,通过比较各兴趣点邻域不变矩的欧式距离提取出初始特征点对,根据几何变换模型剔除伪特征对,最后利用正确映射模型实现图像的拼接。实验表明,该方法对平移以及任意角度的旋转具有良好的鲁棒性,对于具有小尺度变换的图像仍然具有很好的拼接效果。-Abstract: This paper presents a point of interest based on moment invariants (IPIM) of the image stitching technology. Angle using Harris detector to obtain images in the interest of points to calculate the interest point neighborhood of the translation, rotation and scale invariant moments, by comparing the interest point neighborhood of the Continental moment invariants extracted from the initial feature points right, according to the geometric pseudo-transformation model features removed, and finally realize the use of mapping model correctly spliced images. Experiments show that the method of translation and rotation of any angle has good robustness for small-scale transformation of the image still has a good effect splicing.
Update : 2024-04-30 Size : 323584 Publisher : xuyuhua
【Graph Recognize】 1 DL : 0: 摘要：提出了一种新的说话人识别中特征参数的提取方法*在分别使用傅立叶分析和小波分析得到两组特征参数之后，进一步利用+,-./0准则进行参数选取，构造了一种新的混合特征参数*在不增加训练和识别时计算量的同时，结合了傅立叶分析和小波分析两者的优点，具有更好的分类能力*实验结果显示，这种新的混合参数有效地提高了说话人的识别率，能更好地表征说话人的特征*-Abstract: This paper presents a new kind of speaker recognition in the characteristic parameter extraction method*, respectively, using Fourier analysis and wavelet analysis of two sets of characteristic parameters, the further use of 2B !,-./ 0 criteria for parameter selection, construction A new mixed feature parameters* at no additional training and recognition computation At the same time, a combination of Fourier analysis and wavelet analysis of the advantages of both and has better classification capability* Experimental results show that the new mixing parameters effectively enhance the speaker
Update : 2024-04-30 Size : 139264 Publisher : 王功臣
【Graph Recognize】 1 DL : 0: 摘要：一般的说话人识别系统包括特征提取和识别模型两部分，其中特征参数的选择对系统的识别性能有关键性的影响，现就特征提取展开研究，介绍了各种常用的语音特征参数及目前主流的两种参数的提取过程，并论述了小波分析应用于语音特征参数提取中的优势-Abstract: The general speaker recognition system includes feature extraction and recognition model in two parts, of which the choice of the characteristic parameters of the recognition performance of the system have a crucial impact on the feature extraction is to commence the study, introduce a variety of commonly used voice feature parameters and At present, the mainstream of the two parameters of the extraction process, and discusses the wavelet analysis applied to voice characteristic parameter extraction of the advantages of
Update : 2024-04-30 Size : 63488 Publisher : 王功臣
【Other】 KPCA DL : 0: 核主成分分析的特征提取的客户流失预测,大家分享一下.-Kernel Principal Component Analysis of feature extraction of customer churn prediction, to share with Members.
Update : 2024-04-30 Size : 446464 Publisher : 何生
【Graph Recognize】 GABORforrecognition DL : 0: In this article, the feature extract algorithm of Gabor wavelet transform improve the precision
Update : 2024-04-30 Size : 210944 Publisher : 史金玉

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