ConvFormerSR: Fusing transformers and convolutional neural networks for cross-sensor remote sensing imagery super-resolution

Authors

Junjie Li, Wuhan University, China
Yizhuo Meng, University of Southern California
Chongxin Tao, Wuhan University, China
Zhen Zhang, Wuhan University, China
Xining Yang, Eastern Michigan University
Zhe Wang, Wuhan University, China

Document Type

Article

Publication Date

2024

Department/School

Geography and Geology

Publication Title

IEEE Transactions on Geoscience and Remote Sensing

Comments

X. Yang is a faculty member in EMU's Department of Geography and Geology.

Link to Published Version

DOI: 10.1109/TGRS.2023.3340043

Recommended Citation

Li, J., Meng, Y., Tao, C., Zhang, Z., Yang, X., Wang, Z., Wang, X., Li, L., & Zhang, W. (2024). ConvFormerSR: Fusing transformers and convolutional neural networks for cross-sensor remote sensing imagery super-resolution. IEEE Transactions on Geoscience and Remote Sensing, 62, 5601115. https://doi.org/10.1109/TGRS.2023.3340043