Remote Sensing Image Semantic Change Detection Boosted by Semi-Supervised Contrastive Learning of Semantic Segmentation

Semantic change detection (SCD) is a challenging task in remote sensing image (RSI) interpretation, which adopts multitemporal images to detect, locate, and analyze pixel-level land-cover "from-to" changes. In SCD, the severe class imbalance problem and the occurrence of confusing categori...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing Jg. 62; S. 1 - 13
Hauptverfasser:	Zhang, Xiuwei, Yang, Yizhe, Ran, Lingyan, Chen, Liang, Wang, Kangwei, Yu, Lei, Wang, Peng, Zhang, Yanning
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptive sampling Categories Change detection Context Contrastive learning Earth Image segmentation Information processing Land cover Landsat Learning Remote sensing Sampling Self-supervised learning self-training (ST) semantic change detection (SCD) Semantic segmentation Semantics Semi-supervised learning Task analysis Training
ISSN:	0196-2892, 1558-0644
Online-Zugang:	Volltext
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