图 书 馆
流形去噪的流形模糊均值漂移算法Manifold Blurring Mean Shift Algorithms for Manifold Denoising |
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| 课程网址: | http://videolectures.net/cvpr2010_carreira_perpinan_mbms/ |
| 主讲教师: | Miguel Á. Carreira-Perpiñán |
| 开课单位: | 加利福尼亚大学 |
| 开课时间: | 2010-07-19 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We propose a new family of algorithms for denoising data assumed to lie on a low-dimensional manifold. The algorithms are based on the blurring mean-shift update, which moves each data point towards its neighbors, but constrain the motion to be orthogonal to the manifold. The resulting algorithms are nonparametric, simple to implement and very effective at removing noise while preserving the curvature of the manifold and limiting shrinkage. They deal well with extreme outliers and with variations of density along the manifold. We apply them as preprocessing for dimensionality reduction; and for nearest-neighbor classification of MNIST digits, with consistent improvements up to 36% over the original data. |
| 关 键 词: | 模糊均值; 去噪数据; 算法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-03-12：lxf |
| 阅读次数: | 48 |