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Sparse Representation or Collaborative Representation: Which Helps Face Recognition? This code devotes to analyze the working mechanism of SRC, and indicates that it is the CR but not the l1-norm sparsity that makes SRC powerful for face classificati
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基于稀疏表示的人脸识别，里面有9种求1范数的方法-Face recognition based on sparse representation, there are nine kinds of seeking a method of norm
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该源码实现了使用基于稀疏表示的人脸识别算法。使用GPSR作为l1模最小化方法。-This pack of code implement a imges-based face recognition using sparse representation classification. In the algorithm, i employ GPSR as tool to complete the optimization procedure of l1-minimization.
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sparse representation algorithm
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发表于ECCV上的一篇用于人脸识别的算法，Gabor Feature based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary -At ECCV on an algorithm for face recognition, Gabor Feature based Sparse Representation for Face Recognition with Gabor Occlusion Dic
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Matching Pursuit方法，经典的稀疏表示方法，可以用人脸识别和图像分类，图像去噪，现在非常流行。-Matching Pursuit method, sparse representation of the classic, you can use face recognition and image classification, image denoising, now very popular.
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强壮的人脸识别系统，发表于cvpr2011年，程序是应用matlab实现-Recently the sparse representation (or coding) based classifi cation (SRC) has been successfully used in face recognition. In SRC, the testing image is represented as
a sparse linear combination of the trai
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主要用于解决模式识别中稀疏表示人脸识别核心问题L1范数源代码，程序采用同伦算法设计的，在目前稀疏表示多种算法中，同伦算法是性能公认最好的.-Mainly used to solve the sparse representation of face recognition pattern recognition in the core of L1 norm source code, the program designed using the homotopy algorithm, sparse
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Sparse Representation or Collaborative Representation Which Helps Face Recognition
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人脸识别的稀疏表示识别方法将稀疏表示的保真度表示为余项的L2范数，但最大似然估计理论证明这样的假设要求余项服从高斯分布，实际中这样的分布可能并不成立，特别是当测试图像中存在噪声、遮挡和伪装等异常像素，这就导致传统的保真度表达式所构造的稀疏表示模型对上述这些情况缺少足够的鲁棒性。而最大似然稀疏表示识别模型则基于最大似然估计理论，将保真度表达式改写为余项的最大似然分布函数，并将最大似然问题转化为一个加权优化问题-Recently the sparse representation (or codin
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稀疏表示和协同编码哪个对人脸识别起到了决定作用。在稀疏表示的人脸识别中，到底是因为稀疏表示的作用还是他们之间的协同编码起了作用。-Sparse Representation or Collaborative Representation: Which Helps Face Recognition ICCV2011
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illumination-robust face recognition via sparse representation
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用matlab实现的基于稀疏表示的人脸识别方法。其中解稀疏表示时，包含了各种方法。-Using matlab face recognition method based on sparse representation. Solution of the sparse representation, contains a variety of methods.
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稀疏表示在鲁棒性人脸识别中的应用，很经典的论文-Sparse representation in the robustness of face recognition, very classic papers
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一种局部敏感的核稀疏表示分类算法_张石清_赵小明_楼宋江_闯跃龙_郭文平_陈盈
一种融合多模式韦伯局部特征的人脸识别方法_李昆明
自适应阈值及加权局部二值模式的人脸识别_张洁玉-A topical sensitive nuclear sparse representation classification algorithm _ _ House Song Jiang Zhao Xiaoming Zhang Shiqing _ _ _ Chuang Chen Ying Guo Wenpin
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稀疏表示用于人脸识别，采用SDR方法，文字发表在IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE顶级期刊，影响因子4.75.-Sparse representation for face recognition, the use of the SDR method, text published in the IEEE Transactions on pattern analysis and machine intell
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Face recognition via Weighted Sparse Representation Face recognition via Weighted Sparse Representation
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This project describes the problem of facial expression recognition in the field of computer vision. Firstly, the psychological background of the problem is presented. Then, the idea of facial expression recognition system (FERS) is outlined and the
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稀疏表示经典著作
John Wright et al, Robust Face Recognition via Sparse Representation , PAMI 2009的程序-# impFaceRecognition
A Matlab implementation of Face Recognition using Sparse Representation the original paper:
John Wright et al, Robust F
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稀疏表示的毕业参考论文，在图像去噪、图像修复、人脸识别及压缩感知等图像处理领域中的应用进行了总结.-Sparse representation of graduation reference papers, summarized in the image denoising, image restoration, face recognition and compressed sensing and other image processing applications
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