文件名称:Approximate low-rank projection1
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在文中，提出来一个基于低秩的特征提取方法(Feature extraction plays a significant role in pattern
recognition. Recently, many representation-based feature extraction methods have been proposed and achieved successes in many
applications. As an excellent unsupervised feature extraction
method, latent low-rank representation (LatLRR) has shown
its power in extracting salient features)
recognition. Recently, many representation-based feature extraction methods have been proposed and achieved successes in many
applications. As an excellent unsupervised feature extraction
method, latent low-rank representation (LatLRR) has shown
its power in extracting salient features)
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下载文件列表
| 文件名 | 大小 | 更新时间 |
|---|---|---|
| Approximate low-rank projection\Approximate Low-Rank Projection Learning for Feature Extraction.pdf | 2755969 | 2019-12-26 |
| Approximate low-rank projection\Supervised\Pre_label.m | 332 | 2015-08-24 |
| Approximate low-rank projection\Supervised\Recognition_LatLRR.m | 1852 | 2016-03-02 |
| Approximate low-rank projection\Unsupervised\Improve_LRR.m | 1724 | 2015-06-21 |
| Approximate low-rank projection\Supervised | 0 | 2020-01-21 |
| Approximate low-rank projection\Unsupervised | 0 | 2020-01-21 |
| Approximate low-rank projection | 0 | 2020-02-01 |
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