EXPLAINING A DEEP SPATIOTEMPORAL LAND COVER CLASSIFIER WITH ATTENTION AND REDESCRIPTION MINING

Autor: N. Méger, H. Courteille, A. Benoit, A. Atto, D. Ienco

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B3-2022, Pp 673-680 (2022)

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

Externí odkaz: https://doaj.org/article/1df0fb2862c34b59aca4c8bff1b7fbc8

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