Encouraging the Mutual Interact Between Dataset-Level and Image-Level Context for Semantic Segmentation of Remote Sensing Image-Reference-Cited by-同舟云学术

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Encouraging the Mutual Interact Between Dataset-Level and Image-Level Context for Semantic Segmentation of Remote Sensing Image

Published:2024 Issue: Volume:62 Page:1-16
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

An Ke¹^ORCID,Wang Yupei¹^ORCID,Chen Liang¹^ORCID

Affiliation:

1. Beijing Institute of Technology, Beijing, China

Funder

National Natural Science Foundation of China

MYHT Program

National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10388356.pdf?arnumber=10388356

Reference72 articles.

1. Classification for High Resolution Remote Sensing Imagery Using a Fully Convolutional Network

2. Algorithms for semantic segmentation of multispectral remote sensing imagery using deep learning

3. A Multi-Attention UNet for Semantic Segmentation in Remote Sensing Images

4. MAFF-HRNet: Multi-Attention Feature Fusion HRNet for Building Segmentation in Remote Sensing Images

5. RSSFormer: Foreground Saliency Enhancement for Remote Sensing Land-Cover Segmentation

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