Low‐rank nonnegative sparse representation and local preservation‐based matrix regression for supervised image feature selection
Abstract Matrix regression has attracted much attention due to directly select some meaningful features from matrix data. However, most existing matrix regressions do not consider the global and local structure of the matrix data simultaneously. To this end, we propose a low‐rank nonnegative sparse...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-11-01
|
| Series: | IET Image Processing |
| Online Access: | https://doi.org/10.1049/ipr2.12281 |