Learning a Transferable Change Rule from a Recurrent Neural Network for Land Cover Change Detection
When exploited in remote sensing analysis, a reliable change rule with transfer ability can detect changes accurately and be applied widely. However, in practice, the complexity of land cover changes makes it difficult to use only one change rule or change feature learned from a given multi-temporal...
Main Authors: | Haobo Lyu, Hui Lu, Lichao Mou |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2016-06-01
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Series: | Remote Sensing |
Subjects: | |
Online Access: | http://www.mdpi.com/2072-4292/8/6/506 |
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