Land cover classification from multi-temporal, multi-spectral remotely sensed imagery using patch-based recurrent neural networks

Environmental sustainability research is dependent on accurate land cover information. Even with the increased number of satellite systems and sensors acquiring data with improved spectral, spatial, radiometric and temporal characteristics and the new data distribution policy, most existing land cov...

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Vydáno v:	Neural networks Ročník 105; s. 346 - 355
Hlavní autoři:	Sharma, Atharva, Liu, Xiuwen, Yang, Xiaojun
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Elsevier Ltd 01.09.2018
Témata:	Deep learning Land cover classification LSTMs Multi-temporal remote sensing imagery Patch-based RNNs Spatial context Deep learning Land cover classification Patch-based RNNs Multi-temporal remote sensing imagery LSTMs Spatial context
ISSN:	0893-6080, 1879-2782, 1879-2782
On-line přístup:	Získat plný text
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