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个人信息Personal Information
副教授 硕士生导师
招生学科专业：
光学工程 -- 【招收硕士研究生】 -- 航天学院
航空宇航科学与技术 -- 【招收硕士研究生】 -- 航天学院
电子信息 -- 【招收硕士研究生】 -- 航天学院
机械 -- 【招收硕士研究生】 -- 航天学院
性别：男
毕业院校：武汉大学
学历：博士研究生毕业
学位：工学博士学位
所在单位：航天学院
办公地点：航天学院B409
电子邮箱：
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遥感图像智能处理，深度学习，半监督学习，遥感图像云检测和去除、目标检测、语义分割
- .J. Li, Z. Wu, Q. Sheng, B.Wang, Z. Hu, S. Zheng, G. Camps-Vall, M. Molinier, “A hybrid generative adversarial network for weakly-supervised cloud detection in multispectral images,” Remote Sens. Environ., vol. 280, 113197, Oct. 2022. https://doi.org/10.1016/j.rse.2022.113197.(SCI 一区TOP)
- .J. Li, Y. Zhang, Q. Sheng, Z. Wu, B. Wang, Z. Hu, G. Shen, M. Schmitt, M. Molinier, “Thin Cloud Removal Fusing Full Spectral and Spatial Features for Sentinel-2 Imagery,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 8759-8775, 2022, doi: 10.1109/JSTARS.2022.3211857.(SCI 二区)
- .J. Li, Z. Wu, Z. Hu, C. Jian, S. Luo, L. Mou, X. Zhu and M. Molinier, “A Lightweight Deep Learning-Based Cloud Detection Method for Sentinel-2A Imagery Fusing Multiscale Spectral and Spatial Features,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-19, 2022, Art no. 5401219, http://doi.org/10.1109/TGRS.2021.3069641.(SCI 一区TOP, ESI高被引论文)
- .J. Li, Z. Wu, Z. Hu, Z. Li, Y. Wang, and M. Molinier, “Deep learning based thin cloud removal fusing vegetation red edge and short wave infrared spectral information for Sentinel-2A imagery,” Remote Sens., vol. 13, no. 1, p. 157, Jan. 2021, http://doi.org/10.3390/rs13010157.
- .J. Li, Z. W, Z. Hu, J. Z, M. Li, L. Mo and M. Molinier, “Thin cloud removal in optical remote sensing images based on generative adversarial networks and physical model of cloud distortion,” ISPRS J. Photogramm. Remote Sens., vol. 166, pp. 373–389, Aug. 2020, http://doi.org/10.1016/j.isprsjprs.2020.06.021.
- .Z. Wu, J. Li, Y. Wang, Z. Hu and M. Molinier, "Self-Attentive Generative Adversarial Network for Cloud Detection in High Resolution Remote Sensing Images," in IEEE Geoscience and Remote Sensing Letters, vol. 17, no. 10, pp. 1792-1796, Oct. 2020, http://doi.org/10.1109/LGRS.2019.2955071.
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