Rethinking Transformers for Semantic Segmentation of Remote Sensing Images

Transformer has been widely applied in image processing tasks as a substitute for convolutional neural networks (CNNs) for feature extraction due to its superiority in global context modeling and flexibility in model generalization. However, the existing transformer-based methods for semantic segmen...

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Vydané v:	IEEE transactions on geoscience and remote sensing Ročník 61; s. 1 - 15
Hlavní autori:	Liu, Yuheng, Zhang, Yifan, Wang, Ye, Mei, Shaohui
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Ablation Aggregation Artificial neural networks Coders Context Current transformers Decoding Encoder–decoder structure Feature extraction global-local transformer Image acquisition Image processing Image segmentation Information processing Modelling Modules Neural networks Remote sensing remote sensing (RS) Representations Semantic segmentation Semantics Task analysis Visualization
ISSN:	0196-2892, 1558-0644
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