南京航空航天大学主页平台管理系统 LiJun--Home--Paper Publications

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[1].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)

[2].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)

[3].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)

[4].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.

[5].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.

[6].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.

[7].J. Li, Z. W, Z. Hu, Z. Yi and M. Molinier, “AUTOMATIC CLOUD DETECTION METHOD BASED ON GENERATIVE ADVERSARIAL NETWORKS IN REMOTE SENSING IMAGES,” ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 885–892, https://doi.org/10.5194/isprs-annals-V-2-2020-885-2020, 2020.

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