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Remote sensing image semantic change detection is a method used to analyze remote sensing images, aiming to identify areas of change as well as categorize these changes within images of the same location taken at different times.
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2018
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R. C. Daudt, B. Le Saux, and A. Boulch, “Fully convolutional siamese networks for change detection,” in
2018
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B. Hou, Q. Liu, H. Wang, and Y. Wang, “From w-net to cdgan: Bitemporal change detection via deep learning techniques,”
2019
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R. C. Daudt, B. Le Saux, A. Boulch, and Y. Gousseau, “Multitask learning for large-scale semantic change detection,”
2019
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J. Chen, Z. Yuan, J. Peng, L. Chen, H. Huang, J. Zhu, Y. Liu, and H. Li, “Dasnet: Dual attentive fully convolutional siamese networks for change detection in high-resolution satellite images,”
2020
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H. Jiang, X. Hu, K. Li, J. Zhang, J. Gong, and M. Zhang, “Pga-siamnet: Pyramid feature-based attention-guided siamese network for remote sensing orthoimagery building change detection,”
2020
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H. Chen and Z. Shi, “A spatial-temporal attention-based method and a new dataset for remote sensing image change detection,”
2020
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2020
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T. Lei, J. Wang, H. Ning, X. Wang, D. Xue, Q. Wang, and A. K. Nandi, “Difference enhancement and spatial–spectral nonlocal network for change detection in vhr remote sensing images,”
2021
Cited alongside, same era.
H. Chen, Z. Qi, and Z. Shi, “Remote sensing image change detection with transformers,”
2021
Cited alongside, same era.
D. Peng, L. Bruzzone, Y. Zhang, H. Guan, and P. He, “Scdnet: A novel convolutional network for semantic change detection in high resolution optical remote sensing imagery,”
2021
Cited alongside, same era.
K. Yang, G.-S. Xia, Z. Liu, B. Du, W. Yang, M. Pelillo, and L. Zhang, “Asymmetric siamese networks for semantic change detection in aerial images,”
2021
Cited alongside, same era.
A. Radford, J. W. Kim, C. Hallacy, A. Ramesh, G. Goh, S. Agarwal, G. Sastry, A. Askell, P. Mishkin, J. Clark
2021
Y. Li, H. Mao, R. Girshick, and K. He, “Exploring plain vision transformer backbones for object detection,” in
2022
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Y. Niu, H. Guo, J. Lu, L. Ding, and D. Yu, “Smnet: symmetric multi-task network for semantic change detection in remote sensing images based on cnn and transformer,”
2023
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S. Tian, X. Tan, A. Ma, Z. Zheng, L. Zhang, and Y. Zhong, “Temporal-agnostic change region proposal for semantic change detection,”
2023
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L. Ding, J. Zhang, H. Guo, K. Zhang, B. Liu, and L. Bruzzone, “Joint spatio-temporal modeling for semantic change detection in remote sensing images,”
2024
Later among the works it cites.
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Cited alongside, same era.
Z. Li, C. Tang, L. Wang, and A. Y. Zomaya, “Remote sensing change detection via temporal feature interaction and guided refinement,”
2022
Cited alongside, same era.
L. Ding, H. Guo, S. Liu, L. Mou, J. Zhang, and L. Bruzzone, “Bi-temporal semantic reasoning for the semantic change detection in hr remote sensing images,”
2022
Cited alongside, same era.
Z. Zheng, Y. Zhong, S. Tian, A. Ma, and L. Zhang, “Changemask: Deep multi-task encoder-transformer-decoder architecture for semantic change detection,”
2022
Cited alongside, same era.
2024
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2024
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F. Liu, D. Chen, Z. Guan, X. Zhou, J. Zhu, Q. Ye, L. Fu, and J. Zhou, “Remoteclip: A vision language foundation model for remote sensing,”
2024
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