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Semantic segmentation is a vital task in the field of remote sensing (RS).
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2017
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2017
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A. M. Lechner, G. M. Foody, and D. S. Boyd, “Applications in Remote Sensing to Forest Ecology and Management,”
2020
Cited alongside, same era.
F. I. Diakogiannis, F. Waldner, P. Caccetta, and C. Wu, “ResUNet-a: A deep learning framework for semantic segmentation of remotely sensed data,”
2020
Cited alongside, same era.
R. Li, S. Zheng, C. Zhang, C. Duan, L. Wang, and P. M. Atkinson, “ABCNet: Attentive bilateral contextual network for efficient semantic segmentation of Fine-Resolution remotely sensed imagery,”
2021
Cited alongside, same era.
A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly, J. Uszkoreit, and N. Houlsby, “An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale,” in
2021
Cited alongside, same era.
Y. Liu, Y. Zhang, Y. Wang, and S. Mei, “Rethinking Transformers for Semantic Segmentation of Remote Sensing Images,”
2023
Later among the works it cites.
J. Chen, J. Mei, X. Li, Y. Lu, Q. Yu, Q. Wei, X. Luo, Y. Xie, E. Adeli, Y. Wang,
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
K. Chen, B. Chen, C. Liu, W. Li, Z. Zou, and Z. Shi, “RSMamba: Remote Sensing Image Classification With State Space Model,”
2024
Closest in time.
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2021
Cited alongside, same era.
J. Wang, Z. Zheng, A. Ma, X. Lu, and Y. Zhong, “LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation,” in
2021
Cited alongside, same era.
R. Li, S. Zheng, C. Zhang, C. Duan, J. Su, L. Wang, and P. M. Atkinson, “Multiattention Network for Semantic Segmentation of Fine Resolution Remote Sensing Images,”
2021
Cited alongside, same era.
X. Ma, X. Zhang, and M.-O. Pun, “A Crossmodal Multiscale Fusion Network for Semantic Segmentation of Remote Sensing Data,”
2022
Cited alongside, same era.
A. Gu, K. Goel, and C. Ré, “Efficiently Modeling Long Sequences with Structured State Spaces,” in
2022
Cited alongside, same era.
L. Wang, R. Li, C. Zhang, S. Fang, C. Duan, X. Meng, and P. M. Atkinson, “UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery,”
2022
Cited alongside, same era.
2023
Cited alongside, same era.
H. Wu, P. Huang, M. Zhang, W. Tang, and X. Yu, “CMTFNet: CNN and Multiscale Transformer Fusion Network for Remote-Sensing Image Semantic Segmentation,”
2023
Cited alongside, same era.
X. Ma, X. Zhang, and M.-O. Pun, “RS3Mamba: Visual State Space Model for Remote Sensing Image Semantic Segmentation,”
2024
Closest in time.
W. Zhou, S.-I. Kamata, H. Wang, M.-S. Wong,
2024
Closest in time.
2024
Closest in time.
H. Chen, J. Song, C. Han, J. Xia, and N. Yokoya, “ChangeMamba: Remote Sensing Change Detection With Spatiotemporal State Space Model,”
2024
Closest in time.
X. Ma, X. Zhang, M.-O. Pun, and M. Liu, “A Multilevel Multimodal Fusion Transformer for Remote Sensing Semantic Segmentation,”
2024
Closest in time.
J. Sui, Y. Ma, W. Yang, X. Zhang, M.-O. Pun, and J. Liu, “Diffusion Enhancement for Cloud Removal in Ultra-Resolution Remote Sensing Imagery,”
2024
Closest in time.
2024
Closest in time.
S. Zhao, H. Chen, X. Zhang, P. Xiao, L. Bai, and W. Ouyang, “RS-Mamba for Large Remote Sensing Image Dense Prediction,”
2024
Closest in time.
H. Zhou, X. Xiao, H. Li, X. Liu, and P. Liang, “Hybrid Shunted Transformer embedding UNet for remote sensing image semantic segmentation,”
2024
Closest in time.