FEST: Feature Enhancement Swin Transformer for Remote Sensing Image Semantic Segmentation-Reference-Cited by-同舟云学术

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FEST: Feature Enhancement Swin Transformer for Remote Sensing Image Semantic Segmentation

Published:2024-05-08 Issue: Volume: Page:1177-1182
ISSN:
Container-title:2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)
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Author:

Zhang Ronghuan¹,Zhao Jing¹,Li Ming²,Zou Qingzhi¹

Affiliation:

1. Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center,Jinan,China

2. Shandong University of Traditional Chinese Medicine,School of Intelligence and Information Engineering,Jinan,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10579968/10579982/10580494.pdf?arnumber=10580494

Reference13 articles.

1. Feature Graph Convolution Network With Attentive Fusion for Large-Scale Point Clouds Semantic Segmentation

2. DWin-HRFormer: A High-Resolution Transformer Model With Directional Windows for Semantic Segmentation of Urban Construction Land

3. A Hierarchical Decoder Architecture for Multilevel Fine-Grained Disaster Detection

4. A Semantic Segmentation Method for Remote Sensing Images based on Deeplab v3

5. Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

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