MINIMAL LEARNING MACHINE IN ANOMALY DETECTION FROM HYPERSPECTRAL IMAGES
Anomaly detection from hyperspectral data needs computationally efficient methods to process the data when the data gathering platform is a drone or a cube satellite. In this study, we introduce a minimal learning machine for hyperspectral anomaly detection. Minimal learning machine is a novel dista...
| Päätekijät: | , , , |
|---|---|
| Aineistotyyppi: | Artikkeli |
| Kieli: | English |
| Julkaistu: |
Copernicus Publications
2020-08-01
|
| Sarja: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Linkit: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/467/2020/isprs-archives-XLIII-B3-2020-467-2020.pdf |