Description: SOM神经网络，可以进行特征提取和模式分类，特别是特征维数较多的情况。-SOM neural network, can feature extraction and classification, in particular characteristic dimension of more. Platform: |
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Author:周刚 |
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Description: 此设计要求能够实现将医学图像进行识别的过程，包括了图像预处理、图像特征提取及分类判决三大模块。在预处理这一步中主要实现的是将彩色图像转换为灰度图像，灰度图像的二值化，直方图修正，去除干扰、噪声以及差异，边缘增强等；第二模块是图像的特征提取。由于对象的物理与几何特性差异，在影像中表现为局部区域的灰度产生明显变化，形成影像特征，而图像特征提取就是对其进行加工、整理、分析、归纳以便提取构成目标影像的特征，得到能反映图像内容区别于其他事物的本质特征；分类判决作为第三模块，则是要在第二步的基础上采用某种分类判别函数与判别规则，通过对目标特征的分析和匹配来识别目标。-this design requirements to achieve medical image identification process, including the image preprocessing, Image feature extraction and classification ruling three modules. This pretreatment step in the main achievement of the color image is converted to grayscale images, the two gray-scale image value, histogram amendment to remove interference and noise variance Edge Enhancement; the second module is the image feature extraction. Because of the physical objects with geometric characteristics difference in the images showed local area Gray significant changes, the video features, feature extraction and image is its processing, compilation, analysis, summarized in order to extract constitute the target image features can be reflected image as distinct from the other characteristics of th Platform: |
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Author:uhih |
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Description: The aim of Optical Character Recognition (OCR) is to classify optical patterns (often contained in a digital image) corresponding to alphanumeric or other characters. The process of OCR involves several steps including segmentation, feature extraction, and classification. This program use Image Processing Toolbox to get it.
For more information, visit: http://www.matpic.com
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Author:ruan |
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Description: SOM神经网络，可以进行特征提取和模式分类，特别是特征维数较多的情况。-SOM neural network, can feature extraction and classification, in particular characteristic dimension of more. Platform: |
Size: 1024 |
Author:周刚 |
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Description: 此设计要求能够实现将医学图像进行识别的过程，包括了图像预处理、图像特征提取及分类判决三大模块。在预处理这一步中主要实现的是将彩色图像转换为灰度图像，灰度图像的二值化，直方图修正，去除干扰、噪声以及差异，边缘增强等；第二模块是图像的特征提取。由于对象的物理与几何特性差异，在影像中表现为局部区域的灰度产生明显变化，形成影像特征，而图像特征提取就是对其进行加工、整理、分析、归纳以便提取构成目标影像的特征，得到能反映图像内容区别于其他事物的本质特征；分类判决作为第三模块，则是要在第二步的基础上采用某种分类判别函数与判别规则，通过对目标特征的分析和匹配来识别目标。-this design requirements to achieve medical image identification process, including the image preprocessing, Image feature extraction and classification ruling three modules. This pretreatment step in the main achievement of the color image is converted to grayscale images, the two gray-scale image value, histogram amendment to remove interference and noise variance Edge Enhancement; the second module is the image feature extraction. Because of the physical objects with geometric characteristics difference in the images showed local area Gray significant changes, the video features, feature extraction and image is its processing, compilation, analysis, summarized in order to extract constitute the target image features can be reflected image as distinct from the other characteristics of th Platform: |
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Author:uhih |
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Description:
并本文对两大类步态识别算法进行了深入研究，其主要内容集中于步态特征的提取和分类器的设计两部分。
在特征提取阶段采用多种不同的方法提取多种不同的步态特征，其中效果较好的是一种基于模型的特征提取方法。本文使用关键点和肢体角度构建人体的骨骼化模型，
并对模型的各项参数提取做了改进，从人体的骨骼化模型中提取人体的静态参数(如身高、步幅等)以及动态参数(如运动过程中关键点的位置、运动轨迹、肢体角度、-and two types of paper gait recognition algorithm for in-depth study Its main contents concentrated in the gait characteristics of the extraction and classification of the design of two parts. Feature extraction stage in the use of different methods of extracting different gait characteristics, the effect of which is a better model-based feature extraction methods. Using the key points and limbs angle Construction human skeleton model and the model parameter extraction made improvements, from the human skeleton model of the human body from the static parameters (such as height, Stride) and dynamic parameters (such as the process of movement key points, trajectory, physical perspective, Platform: |
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Author:QHLee |
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Description: 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 Platform: |
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Author:冷福 |
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Description: 利用Sub-pattern PCA在Yale人脸库上进行人脸识别的matlab源代码，子模式主成分分析首先对原始图像分块，然后对相同位置的子图像分别建立子图像集，在每一个子图像集内使用PCA方法提取特征，建立子空间。对待识别图像，经相同分块后，分别将子图像向对应的子空间投影，提取特征。最后根据最近邻原则进行分类。-Sub-pattern PCA use in the Yale face database for face recognition on the matlab source code, sub-mode principal component analysis first of the original image block, and then the same sub-image, respectively, the location of the establishment of sub-image set, in each sub-image Set the use of PCA to extract the features, the establishment of sub-space. Treatment to identify images, by the same block, the respective sub-image to the corresponding sub-space projection, feature extraction. Finally, according to the principle of nearest neighbor classification. Platform: |
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Author:章格 |
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Description: 一个典型的人脸识别系统主要包括训练过程和识别过程。训练过程主要完成将已知人脸进行定位、特征提取与选择、以及分类器的设计；识别过程则完成将未知图片进行处理，并最终识别出身份的分类和决策-A typical face recognition system mainly include the training process and the identification process. Completion of the training process will be the main face of known position, feature extraction and selection, and classifier design identification process will be completed to deal with the unknown image, and ultimately identify the identity of the classification and decision-making Platform: |
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Author:likunbao |
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Description: matlab图像处理工具相，使用了主成分分析，ANN，SVM等方法。-This toolBox used in the image processing(feature extraction and classification)
PCA,LDA,ICA,DCT,RBF,RBE,GRNN,KNN,minimum distance,SVM, and others Platform: |
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Author:大长今 |
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Description: 此资料实现了ADABOOST和HAAR的特征提取和从弱分类到强分类的具体步骤-The data achieved ADABOOST and HAAR of feature extraction and classification from weak to strong category specific steps Platform: |
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Author:shuyachen |
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Description: Feature Extraction for Speech Processing and SVM Classification of Voice Samples. This package contains Feature Extraction and Classification Matlab codes and some turkish voice records. Platform: |
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Author:Merdem |
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Description: DEAP数据集下的情绪识别分类，包括特征提取和分类(Emotion recognition classification based on deap data set, including feature extraction and classification) Platform: |
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Author:hjcupupup |
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Search - feature extraction and classification