@article{hj2023_kpinet,
title={An Optimization-Driven Network With Knowledge Prior Injection for HSI Denoising},
author={Li, Yajie and Li, Jie and He, Jiang and Liu, Xinxin and Yuan, Qiangqiang},
journal={IEEE Transactions on Geoscience and Remote Sensing},
volume={61},
pages={1--17},
year={2023},
publisher={IEEE}
}


@article{hj2023_sSRPNet,
author = {He, Jiang and Yuan, Qiangqiang and Li, Jie and Xiao, Yi and Zhang, Liangpei},
title = {A self-supervised remote sensing image fusion framework with dual-stage self-learning and spectral super-resolution injection},
journal = {ISPRS Journal of Photogrammetry and Remote Sensing},
volume = {204},
pages = {131-144},
year = {2023},
}


@article{PENG2023303,
title = {Automated glacier extraction using a Transformer based deep learning approach from multi-sensor remote sensing imagery},
author = {Yanfei Peng and Jiang He and Qiangqiang Yuan and Shouxing Wang and Xinde Chu and Liangpei Zhang},
journal = {ISPRS Journal of Photogrammetry and Remote Sensing},
volume = {202},
pages = {303-313},
year = {2023},
}


@article{hj2023_DL4sSR,
title={Spectral super-resolution meets deep learning: achievements and challenges},
author={He, Jiang and Yuan, Qiangqiang and Li, Jie and Xiao, Yi and Liu, Denghong and Shen, Huanfeng and Zhang, Liangpei},
journal={Information Fusion},
volume={97},
pages={101812},
year={2023},
}


@article{xiao2023_degrade,
title={From degrade to upgrade: Learning a self-supervised degradation guided adaptive network for blind remote sensing image super-resolution},
author={Xiao, Yi and Yuan, Qiangqiang and Jiang, Kui and He, Jiang and Wang, Yuan and Zhang, Liangpei},
journal={Information Fusion},
year={2023},
publisher={Elsevier}
}


@article{liu2023_eunet,
title={An Efficient Unfolding Network with Disentangled Spatial-Spectral Representation for Hyperspectral Image Super-Resolution},
author={Liu, Denghong and Li, Jie and Yuan, Qiangqiang and Zheng, Li and He, Jiang and Zhao, Shuheng and Xiao, Yi},
journal={Information Fusion},
volume={94},
pages={92-111},
year={2023},
}


@inproceedings{wang2022ensemble,
title={An Ensemble Learning Approach with Multi-depth Attention Mechanism for Road Damage Detection},
author={Wang, Shouxing and Tang, Yao and Liao, Xusi and He, Jiang and Feng, Haoliang and Jiao, Hongzan and Su, Xin and Yuan, Qiangqiang},
booktitle={2022 IEEE International Conference on Big Data (Big Data)},
pages={6439--6444},
year={2022},
organization={IEEE}
}


@ARTICLE{jin2023learning,
author={Jin, Xianyu and He, Jiang and Xiao, Yi and Yuan, Qiangqiang},
journal={IEEE Geoscience and Remote Sensing Letters},
title={Learning a Local-Global Alignment Network for Satellite Video Super-Resolution},
year={2023},
volume={},
number={},
pages={1-1},
doi={10.1109/LGRS.2023.3250009}
}


@article{hj2022_AGCS,
title={Data-driven multi-source remote sensing data fusion: Progress and challenges},
author={Zhang, Liangpei and He, Jiang and Yang,Qianqian and Xiao,Yi and Yuan, Qiangqiang},
journal={Acta Geodaetica et Cartographica Sinica},
volume={51},
number={7},
pages={1317-1337},
year={2022},
}


@article{xy2022_deepcams,
title={Generating a long-term (2003- 2020) hourly 0.25° global PM2. 5 dataset via spatiotemporal downscaling of CAMS with deep learning (DeepCAMS)},
author={Xiao, Yi and Wang, Yuan and Yuan, Qiangqiang and He, Jiang and Zhang, Liangpei},
journal={Science of The Total Environment},
pages={157747},
year={2022},
publisher={Elsevier}
}


@ARTICLE{hj2022_GRSM,
author={Deng, L.-J. and Vivone, G. and Paoletti, M. E. and Scarpa, G. and He, J. and Zhang, Y. and Chanussot, J. and A. Plaza},
journal={IEEE Geoscience and Remote Sensing Magazine},
title={Machine Learning in Pansharpening: A Benchmark, from Shallow to Deep Networks},
volume={10},
number={3},
pages={279-315},
year={2022},
doi={10.1109/MGRS.2020.3019315}
}


@article{hj2022_pnxnet,
title = { A Knowledge Optimization-driven Network with Normalizer-Free Group ResNet Prior for Remote Sensing Image Pan-sharpening},
author = {He, Jiang and Yuan, Qiangqiang and Li, Jie and Zhang, Liangpei},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
volume = {60},
pages = {1-16},
year = {2022},
doi={10.1109/TGRS.2022.3186916}
}


@InProceedings{arad2022_cvpr,
author = {Arad, Boaz and Timofte, Radu and etal.},
title = {NTIRE 2022 Spectral Recovery Challenge and Data Set},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2022},
pages = {863-881}
}


@article{hj2022_DsTer,
title = {DsTer: A dense spectral transformer for remote sensing spectral super-resolution},
author = {He, Jiang and Yuan, Qiangqiang and Li, Jie and Xiao,Yi and Liu, Xinxin and Zou, Yun},
journal = {International Journal of Applied Earth Observation and Geoinformation},
volume = {109},
pages = {102773},
year = {2022},
}


@article{xy2022_space,
title={Space-time super-resolution for satellite video: A joint framework based on multi-scale spatial-temporal transformer},
author={Xiao, Yi and Yuan, Qiangqiang and He, Jiang and Zhang, Qiang and Sun, Jing and Su, Xin and Wu, Jialian and Zhang, Liangpei},
journal={International Journal of Applied Earth Observation and Geoinformation},
volume={108},
pages={102731},
year={2022},
}


@article{hj2022_ponet,
author = {He, Jiang and Yuan, Qiangqiang and Li, Jie and Zhang, Liangpei},
title = {PoNet: A universal physical optimization-based spectral super-resolution network for arbitrary multispectral images},
journal = {Information Fusion},
volume = {80},
pages = {205-225},
year = {2022},
}


@article{hj2021_hsrnet,
author = {He, Jiang and Li, Jie and Yuan, Qiangqiang and Shen, Huanfeng and Zhang, Liangpei},
title = {Spectral Response Function-Guided Deep Optimization-Driven Network for Spectral Super-Resolution},
journal = {IEEE Transactions on Neural Networks and Learning Systems},
volume = {33},
number = {9},
pages = {4213-4227},
year = {2022},
}


@article{hj2019_wssrn,
author = {He, Jiang and Li, Jie and Yuan, Qiangqiang and Li, Huifang and Shen, Huanfeng},
title = {Spatial-spectral Fusion in Different Swath Widths by a Recurrent Expanding Residual Convolutional Neural Network},
journal = {Remote Sensing},
volume = {11},
number = {19},
pages = {2203},
year = {2019},
}