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SRC 实现了使用基于稀疏表示的人脸识别算法
- 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.
ma yi sparse representation classification
- ma yi sparse representation classification .EXTENDED YALE B database.recognition rate 95 。-ma yi sparse representation classification. recognition rate 95 .
RSC
- 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
LSL_SC
- based classification (SRC) has been widely used for face recognition (FR). SRC first codes a testing sample as a sparse linear combination of all the training samples, and then classifies the testing sample by evaluating which class leads to the mini
spgl1-1.8
- based classification (SRC) has been widely used for face recognition (FR). SRC first codes a testing sample as a sparse linear combination of all the training samples, and then classifies the testing sample by evaluating which class leads to
metasample based sparse representation classification code
- 本matlab源程序适用于论文 metasample-based sparse representation for tumor classification
MSRC_IEEE
- 本程序适用于论文metasample-based sparse representation for tumor classification-this code suite for paper metasample-based sparse representation for tumor classification
SRC_Test
- Sparse representation based classification (SRC John Wright CVPR2009) 实现-Sparse representation based classification (SRC John Wright CVPR2009)‘s codes
FDDL_IJCV
- Sparse Representation based Fisher Discrimination Dictionary Learning for Image Classification
sparse-representation-pdf
- 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
SRC
- SRC-sparse representation-based classifier .基于稀疏表达的分类。-SRC-sparse representation-based classifier. Based on the sparse expression classification.
Hyperspectral-Image-Classification
- 这篇文章主要是讲高光谱分类的，使用基于词典的稀疏算法对高光谱进行分类。-Dictionary-Based, Clustered Sparse Representation for Hyperspectral Image Classification
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)
FDDL
- 基于Fisher字典学习的稀疏表示分类算法。(Sparse representation classification algorithm based on Fisher dictionary learning.)