Description: This package contains the Matlab codes implementing the ScSPM algorithm described in CVPR 09 paper "Linear Spatial Pyramid Matching using Sparse Coding for Image Classification".
-This package contains the Matlab codes implementing the ScSPM algorithm described in CVPR 09 paper "Linear Spatial Pyramid Matching using Sparse Coding for Image Classification". Platform: |
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Author:qinlei |
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Description: 基于稀疏编码和线性塔式匹配的图像分类算法。-This package contains the Matlab codes implementing the ScSPM algorithm described in CVPR 09 paper "Linear Spatial Pyramid Matching using Sparse Coding for Image Classification".
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Author:sinoer |
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Description: 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 coding) based classification (SRC) has been successfully used in face recognition. In SRC, the testing image is represented as a sparse linear combination of the training samples, and the representation fidelity is measured by the 𝑙 2-norm or 𝑙 1-norm of coding residual. Such a sparse coding model actually assumes that the coding residual follows Gaussian or Laplacian distribution, which may not be accurate enough to describe the coding errors in practice. In this paper, we propose a new scheme, namely the robust sparse coding (RSC), by modeling the sparse coding as a sparsityconstrained
robust regression problem. The RSC seeks for the MLE (maximum likelihood estimation) solution of the
sparse coding problem, and it is much more robust to outliers (e.g., occlusions, corruptions, etc.) than SRC. An efficient iteratively reweighted sparse coding algorithm is
proposed to solve the RSC model. Platform: |
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Author:徐波 |
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Description: 本文实现了09年CVPR的文章Linear Spatial Pyramid Matching using Sparse Coding for Image Classification-This package contains the Matlab codes implementing the ScSPM algorithm described in CVPR 09 paper
"Linear Spatial Pyramid Matching using Sparse Coding for Image Classification".
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Author:123 |
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Description: 自主学习把稀疏自编码器和分类器实现结合。先通过稀疏自编码对无标签的5-9的手写体进行训练得到最优参数，然后通过前向传播，得到训练集和测试集的特征，通过0-4有标签训练集训练出softmax模型，然后输入测试集到分类模型实现分类。-Independent Learning the encoder and the sparse classifiers achieve the combination. First through sparse coding since no label was handwritten 5-9 training obtain the optimal parameters, and then through the front propagation, get the training and test sets of features, a label by 0-4 trained softmax model train set, then enter the test set to the classification model to classify. Platform: |
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Author:单清序 |
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Description: 稀疏编码能够快速，准确，低代价地表示自然图像的视觉神经方面的能力，把稀疏编码的方法运用到分类中的机器学习方法，就叫做SRC。此处提供SRC算法代码。-Sparse coding has the rapid, accurate and low cost ability to display natural images. The method of sparse coding is applied to the classification of machine learning methods and this is SRC. Here is the SRC algorithm code. Platform: |
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Author:范婷 |
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Description: This package contains the Matlab codes implementing the ScSPM algorithm described in CVPR 09 paper
Linear Spatial Pyramid Matching using Sparse Coding for Image Classification .基于空间金字塔匹配的稀疏编码，用于图像检索，识别与分类-This package contains the Matlab codes implementing the ScSPM algorithm described in CVPR' 09 paper " Linear Spatial Pyramid Matching using Sparse Coding for Image Classification" . Based on the spatial pyramid matching sparse coding for image retri , identification and classification Platform: |
Size: 19136512 |
Author:吃鱼的小猫鼠 |
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Description: KSVD 算法 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(KSVD algorithm K-SVD sparse data is represented by building dictionaries, often used for image compression, coding, classification, and other applications) Platform: |
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Author:哈哈星星
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Description: 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.) Platform: |
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Author:曹志民
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Description: 使用迁移学习和稀疏编码来实现不同领域之间的适配，是一种基于特征表示的迁移学习(This method is designed for image clustering and classification and called sparse subspace clustering.) Platform: |
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Author:Jushua |
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