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...
| Huvudupphovsmän: | , , , |
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| Materialtyp: | Artikel |
| Språk: | English |
| Publicerad: |
Copernicus Publications
2020-08-01
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| Serie: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Länkar: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/467/2020/isprs-archives-XLIII-B3-2020-467-2020.pdf |