搜索资源列表
IALM
- 基于不精确拉格郞日算子法的低秩矩阵重构程序，可以用于图像分割，将目标图像分割为背景和前景，从而将前景分离出来。-Lagrangian method based on imprecise low rank matrix reconstruction procedures can be used for image segmentation, the target image into background and foreground, which will separate the foregr
lrsdrpca
- 基于LRSD方法的低秩图像分解程序，参数可以在运行中依据目标图像的实际情况进行调节，注意目标图像不要过大，否则会溢出。-Image decomposition process based on low rank LRSD method parameters can be based on the actual situation in the operation of the target image is adjusted, note the target image is not too l
svtrpca
- 基于特征值分解的低秩图像分解程序，将目标图像分割为背景和前景之和，参数可以在运行中依据目标图像的实际情况进行调节，注意目标图像不要过大，否则会溢出。-Based on Eigenvalue Decomposition of low rank image decomposition process, the target image into the background and the foreground and, in the operation parameters can be base
CompressiveAndApplications
- 《压缩感知与应用》源代码，包含SAR图像压缩感知、高光谱压缩感知、基于结构稀疏的SAR图像低秩重建- Compressed sensing and application source code, including SAR image compressive sensing, hyperspectral image compression, based on the structure of sparse SAR image low rank reconstruction
Nonlocal-Image-Restoration-
- 利用非局部特性并结合低秩解法的图像降噪算法，速度很快-Nonlocal properties combined with low rank Solution image noise reduction algorithm, fast
RASL_Code_CPP
- 鲁棒人脸识别的低秩表示,用来解决批量的人脸对齐问题。-Learning Low-Rank Representations with Classwise Block-Diagonal Structure for Robust Face Recognition
sparse_graph_LRR
- 关于文献“ Laplacian Regularized Low-Rank Representation and Its Applications”的matlab 源码-with regard to the paper Laplacian Regularized Low-Rank Representation and Its Applications matlab code
lrr
- 求解低秩表示模型。使用ADM求解样本的低秩表示矩阵。-Solving low rank representation model.
Latent-LRR
- 由文章作者提供的隐式低秩子空间聚类算法。参考文献：Guangcan Liu, Shuicheng Yan. Latent low rank representation [J]. Springer International Publishing, 2014:23-38. -The program is provided by the authors to realize latent low rank subspace clustering. Reference: Guangcan Liu,
lrr(motion_face)
- 本程序是用来处理图像，把代表图像的矩阵分解成为一个低秩矩阵和一个稀疏矩阵~-This procedure is used to deal with the image, the representative image of the matrix decomposed into a low-rank matrix and a sparse matrix ~
paper2
- Channel Estimation for Millimeter Wave MIMO-OFDM Systems via Low-Rank Tensor Decomposition
LRR-and-WNNM-LRR
- 该程序可实现低秩子空间聚类和加权核范数最小化低秩子空间聚类。参考文献：Guangcan Liu, Zhouchen Lin, Shuicheng Yan, Ju Sun, Yong Yu, Yi Ma, Robust recovery of subspace structures by low-rank representation, IEEE T. Pattern Anal. 35(1) (2013) 171-184.-This program can realize subspace clu
Randomized_LU
- Randomized LU Decomposition Low rank approximation using randomized LU decomposition
sparse-denoise
- 使用图像的低秩约束去除图像中稀疏噪声，同时施加了噪声的稀疏约束-The use of images of low rank constraint removed sparse image noise while applying noise sparse constraint
RMSC
- Robust Multi-View Spectral Clustering via Low-Rank and Sparse Decomposition
SVT
- SVT 低秩矩阵恢复，可用于稀疏表示、图像恢复(SVT for low rank matrix completion)
code of transfer learning code
- 基于低秩和稀疏表达的迁移子空间学习算法的代码(A migration subspace learning algorithm based on low rank and sparse representation)
稀疏分解图像去噪
- 基于稀疏字典和稀疏编码的图像去噪算法，基于低秩约束的高光谱条纹噪声去除，包含论文及代码(Based on sparse dictionary and sparse coding image denoising algorithm, based on low rank constraints of hyperspectral fringe noise removal, including papers and code)
ICCV-MoG
- 孟德宇老师的低秩分解代码，对动态变化的视频帧提取它的低秩背景，同时得到它的稀疏部分。利用混合高斯对误差进行建模(Teacher Meng Deyu's low rank decomposition code extracts the low rank background of the dynamic video frame and obtains the sparse part of it. The error is modeled by mixed Gauss)
程序
- 以稀疏子空间聚类以及低秩子空间聚类等基本谱聚类算法为基础，通过 运用核映射算法，融合与数据本身结构相关的局部切线空间函数以及主成分分析 算法建立了可以应对独立子空间聚类、非独立子空间聚类、非线性聚类、混合多 流体聚类问题以及多种含有大数据量的实际问题，包括处理运动分割、人脸识别、 工件识别等情况中的多种类型数据分类的聚类算法，并且引入 Map-Reduce 并行处 理方法优化了算法的计算效率(Based on the basic spectral clustering algorith