A Multi-Scale Water Extraction Convolutional Neural Network (MWEN) Method for GaoFen-1 Remote Sensing Images
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Title
A Multi-Scale Water Extraction Convolutional Neural Network (MWEN) Method for GaoFen-1 Remote Sensing Images
Authors
Keywords
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Journal
ISPRS International Journal of Geo-Information
Volume 9, Issue 4, Pages 189
Publisher
MDPI AG
Online
2020-03-26
DOI
10.3390/ijgi9040189
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- Identification of Water Bodies in a Landsat 8 OLI Image Using a J48 Decision Tree
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- (2011) Xianfeng Song et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
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