EXPLAINING A DEEP SPATIOTEMPORAL LAND COVER CLASSIFIER WITH ATTENTION AND REDESCRIPTION MINING
Deep learning-based land cover classifiers learnt from Satellite Image Time Series (SITS) are known to reach high performances. In order to explain, at least partly, the rationale leading to each one of their decisions, attention-based architectures have been proposed to automatically weight the imp...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2022-05-01
|
Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2022/673/2022/isprs-archives-XLIII-B3-2022-673-2022.pdf |