搜索资源列表
MatchingPursuits
- 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.
SRC
- Sparse Representation for accurate classification of corrupted and occluded facial expressions使用稀疏表示方法对有遮挡和腐蚀的人脸表情图像进行分类-Sparse Representation for accurate classification of corrupted and occluded facial expressions
SolvePFP
- 图像等运用稀疏表示的方法进行计算识别和分类-Images using sparse representation method to calculate identification and classification
SparseRepresentationaItsApplication
- 稀疏表达及其应用的简单介绍，其中涵盖了稀疏表示、特征提取、压缩感知、图像增强、盲源分离、模式分类、目标跟踪和图像超分辨等。PPT和PDF是对应的，并添加了可视化的结果。-Sparse Representation and Its Application: Compressive Sensing, Visual Feature, Image Enhancement, Blind Source Separation, Pattern Classification, Object Tracking a
- 对场景分类和语义特征稀疏化的高层图像表示-Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification
Sparse_Representations_classifier
- 一个常用的稀疏表示分类器，SRC分类器，用于信号或图像分类，需共同配合CVX运行，可见示例example.m。-Applying for Sparse Representaion Classification with the method SRC， cooperating with the CVX file. See example.m for a trying run.
Image-Super-Resolution-Algorithms
- 前基于图像块稀疏表示的超分辨率重构算法对所有图像块都用同一字典表示，不能反映不同类型图 像块问的筹别．针对这一缺点，本文提出基于图像块分类稀疏表示的方法．该方法先利用图像局部特征将图像块分为 平滑、边缘和不规则结构三种类型，其中边缘块细分为多个方向．然后利用稀疏表示方法对边缘和不规则结构块分别 训练各自对应的低分辨率和-岛分辨率字典．重构时对平滑块利用简单双三次插值方法，边缘和不规则结构块由其对应 的高、低分辨率字典通过正交匹配追踪箅法重构．实验结果表明，与单字典稀疏表示算法相比
SRC
- 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
EA-SRC
- 利用超限学习机（ELM）和稀疏表示(SRC)进行图像分类。Matlab完整源码。-Extreme learning machine and adaptive sparse representation for image classification
ksvdsbox11-min
- 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)
eccv10_tutorial_part2
- 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.)
RSC
- 只要是使用稀疏表示方法进行的图像分类，非常有用！(It is useful as long as it is an image classification using the sparse representation method!)
AnalysisKSVDbox
- 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
Fisher字典学习
- 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.)
Indian
- 使用基于词典的稀疏表示高光谱图像分类,多任务联合稀疏表示和逐步MRF优化的高光谱图像分类(Dictionary-based sparse representation hyperspectral image classification, multi-task joint sparse representation and stepwise MRF optimized hyperspectral image classification)
SRC_SOMP_matlab-master
- 稀疏表示分类器应用于高光谱图像分类的MATLAB代码实现(MATLAB Code Implementation of Sparse Representation Classifier for Hyperspectral Image Classification)