搜索资源列表
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ma yi sparse representation classification .EXTENDED YALE B database.recognition rate 95 。-ma yi sparse representation classification. recognition rate 95 .
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运用harr特征+SRC（稀疏表示）分类实现的一种车辆检测方法，文件中提供了训练和测试车辆图片。由于时间原因，所用haar特征没有优化，维度过高，导致滑窗框图过慢，本代码只输出效果统计数据，以供大家参考学习稀疏表示在车辆检测中的应用。-Using harr feature+SRC (sparse representation) classification to achieve a vehicle detection method, the paper provides a training a
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based classification (SRC) has been widely used for face recognition (FR). SRC first codes a testing sample as a sparse linear combination of all the training samples, and then classifies the testing sample by evaluating which class leads to the mini
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based classification (SRC) has been widely used for face
recognition (FR). SRC first codes a testing sample as a
sparse linear combination of all the training samples, and
then classifies the testing sample by evaluating which class
leads to
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本matlab源程序适用于论文 metasample-based sparse representation for tumor classification
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此程序为袁晓彤CVPR论文“基于多任务联合稀疏表示的的视觉分类”的主代码部分-The program for Yuan Xiaotong CVPR paper " visual classification with Muti-task joint sparse representation" main code of the parts
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一个自己编的稀疏表示分类程序（SRC），以帮助了解SRC的原理和算法。-A self sparse representation classification (SRC) program, to help understand the principles and algorithms of the SRC.
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极限学习机\极速学习机\ELM
稀疏表示人脸识别\稀疏表示\L0范数求解
基于ELM与稀疏表示的混合人脸识别算法
AR人脸识别准确率95 .
文章:Luo, Minxia, and Kai Zhang. A hybrid approach combining extreme learning machine and sparse representation for image classification. Engineering Applications of Artific
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Sparse representation based classification (SRC John Wright CVPR2009) 实现-Sparse representation based classification (SRC John Wright CVPR2009)‘s codes
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matlab中的cvx工具包,适用于windows64位系统，在信号的稀疏表示分类领域有很大的用处，网络上有此工具包的安装说明，1要先解压2移动到matlab的一个空文件夹下3打开matlab，将当前路径设置为此文件夹下的cvx文件夹4在命令行窗口输入cvx_setup-matlab in cvx toolkit for windows64 bit systems, in a sparse representation of the signal areas of the classificat
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Recent research has shown the speed advantage of extreme learning machine (ELM) and the accuracy
advantage of sparse representation classification (SRC) in the area of image classification. Those two
methods, however, have their respective drawback
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稀疏编码图像分类, 稀疏表示创始人写的PPT,内容精彩,分析清晰,易于理解(sparse coding image classification, PPT written by the original author of sparse representation, the PPT content is easy to realize with clear illustration and analysis.)
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K-SVD可以看做K-means的一种泛化形式，K-means算法总每个信号量只能用一个原子来近似表示，而K-SVD中每个信号是用多个原子的线性组合来表示的。
K-SVD通过构建字典来对数据进行稀疏表示，经常用于图像压缩、编码、分类等应用。(K-SVD can be regarded as a generalized form of K-means. The total K-means algorithm can only approximate one signal for each sem
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基于稀疏表示的高光谱图像分类的Fisher字典学习方法matlab代码(Hypersynthetic image classification based on sparse representation in Fisher dictionary learning matlab code.)
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基于Fisher字典学习的稀疏表示分类算法。(Sparse representation classification algorithm based on Fisher dictionary learning.)
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