搜索资源列表
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4下载：
基于字典学习的稀疏编码，最新的版本，可以用于 window Linux和MacOs-Sparse Coding on Dictionary Learning，the new version. it can be applied to the windows, Linux and Mac
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多种信号过完备字典学习算法的工具包，包含文献Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms中所有的算法。-Multiple signals over-complete dictionary learning algorithm toolkit, including literature Surveying and comparing simultaneous sparse
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CS理论里观测矩阵的优化算法以及训练稀疏字典的算法-optimization of measurement matrix and dictionary learning for sparse approximations
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Metaface Learning for Sparse Fisher Discrimination Dictionary Learning for Sparse Representation
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用基于稀疏表示和KSVD字典学习去噪方法在对数域对SAR图像抑斑，本方法相对于一些经典的SAR图像抑斑方法，抑斑效果大大提高。-Based on the sparse representation and KSVD dictionary learning denoising method in the logarithmic domain，we despeckle SAR image, compared with some of the classic SAR image speckle sup
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參考文獻「Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering」
Clustering-based Sparse Representation 的 matlab代碼-「Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering」and
Clustering-based Sparse
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该算法是K-SVD算法的一种改进算法。该算法可以用于稀疏字典的学习中。与传统方法相比，能够有效的降低计算量，提高字典更新的速度。-The algorithm is an improved algorithm of K-SVD algorithm. The algorithm can be used to sparse dictionary learning. Compared with conventional methods, it is possible to effectively red
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SMALLbox，这个工具箱不仅用来比较各种稀疏表示的解法，而且把字典学习算法也融合了进去-SMALLbox, the toolbox not only be used to compare various sparse representation of the solution, and the dictionary learning algorithm also combines into
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2012 ECCV 稀疏编码和 字典学习- Sparse Coding and Dictionary Learning for Symmetric Positive Definite Matrices: A Kernel Approach.
European Conference on Computer Vision (ECCV), pp. 216-229, 2012.
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稀疏表示，字典学习，KSVD算法，matlab版-Sparse representation dictionary learning, KSVD algorithm, matlab
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这是一篇SCI文章《改善字典学习：多字典更新和系数重用》里的Matlab代码，包含了OMP、Batch-OMP、CoROMP等匹配跟踪算法代码以及改进的K-SVD字典学习算法代码，是图像稀疏表示研究方向重要的源代码，有助于大家学习和改进。-This file folder reproduces the Figures for paper:"Improving Dictionary Learning: Multiple Dictionary Updates and Coefficient Reus
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应用局部表示进行图像显著度检测，该方法不需要事先学习字典。-local sparse representation for detecting image saliency with out learning a dictionary.
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Weisheng Dong and Xin Li. "Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering"基于聚类的图像稀疏去噪这篇论文的去噪代码。-Weisheng Dong and Xin Li. " Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering" C
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focuss算法 关于图像稀疏性分解中字典学习的经典算法-focuss on the image sparse decomposition algorithm in the classical dictionary learning algorithms
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基于稀疏表示和字典的分割,稀疏表示和字典分割来分割医学图像-Deformable segmentation via sparse representation and dictionary learning
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稀疏表示，字典学习，初学者，KSVD-Sparse representation dictionary learning, beginners, KSVD etc.
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使用基于稀疏表示和字典学习的图像去噪研究方法，比一般的帧间差分算法等要高效。-Sparse representation and dictionary-based learning denoising methods, than the average frame difference algorithm to be efficient.
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这是关于稀疏字典学习用于人脸识别图像处理的文章，里面是对应的算法代码-This is an article about sparse dictionary learning for face recognition image processing, which is the corresponding algorithm code
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利用非参数贝叶斯字典学习模型进行图像稀疏表示(use non-parametric-bayesian-dictionary-learning-for-sparse-image-representations)
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压缩感知，在线字典学习，稀疏编码，矩阵优化(Compression perception, online dictionary learning, sparse coding, matrix optimization)
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