[8] Q. Zhang, Q. Yuan, J. Li, Y. Wang, F. Sun, and L. Zhang, “Generating seamless global daily AMSR2 soil moisture (SGD-SM) long-term products for the years 2013-2019,” Earth System Science Data (ESSD), vol. 13, pp. 1385–1401, 2021. (SCI Q1 Top, IF=9.197) [PDF] [Project] [Dataset] [Code] [BibTeX]

[7] Q. Zhang, Q. Yuan, Z. Li, F. Sun, and L. Zhang, “Combined deep prior with low-rank tensor SVD for thick cloud removal in multitemporal images,” ISPRS Journal of Photogrammetry and Remote Sensing (ISPRS P&RS), in press, 2021. (SCI Q1 Top, IF=7.319) [PDF] [Dataset] [BibTeX]

[6] Q. Zhang, Q. Yuan, J. Li, F. Sun, and L. Zhang, “Deep spatio-spectral Bayesian posterior for hyperspectral image non-i.i.d. noise removal,” ISPRS Journal of Photogrammetry and Remote Sensing (ISPRS P&RS), vol. 164, pp. 125-137, 2020. (SCI Q1 Top, IF=7.319) [PDF] [Dataset] [BibTeX]

[5] Q. Zhang, Q. Yuan, J. Li, Z. Li, H. Shen, and L. Zhang, “Thick cloud and cloud shadow removal in multitemporal images using progressively spatio-temporal patch group deep learning,” ISPRS Journal of Photogrammetry and Remote Sensing (ISPRS P&RS), vol. 162, pp. 148-160, 2020. (SCI Q1 Top, IF=7.319) [PDF] [Code] [Dataset] [BibTeX]

[4] Q. Zhang, Q. Yuan, J. Li, X. Liu, H. Shen, and L. Zhang, “Hybrid noise removal in hyperspectral imagery with spatial-spectral gradient network,” IEEE Transactions on Geoscience and Remote Sensing (TGRS), vol. 57, no. 10, pp. 7317-7329, 2019. (SCI Q1 Top, IF=5.855) [PDF] [Dataset] [BibTeX]

[3] Q. Zhang, Q. Yuan, C. Zeng, X. Li, and Y. Wei, “Missing data reconstruction in remote sensing image with a unified spatial-temporal-spectral deep convolutional neural network,” IEEE Transactions on Geoscience and Remote Sensing (TGRS), vol. 56, no. 8, pp. 4274-4288, 2018. (SCI Q1 Top, IF=5.855, ESI Highly Cited Paper) [PDF] [Code] [BibTeX] [Citations: 100+]

[2] Q. Zhang, Q. Yuan, J. Li, Z. Yang, and X. Ma, “Learning a dilated residual network for SAR image despeckling,” Remote Sensing (RS), vol. 10, no. 2, 196, 2018. (SCI Q2, IF=4.509) [PDF] [BibTeX]

[1] Q. Yuan, Q. Zhang, J. Li, H. Shen, and L. Zhang, “Hyperspectral image denoising employing a spatial-spectral deep residual convolutional neural network,” IEEE Transactions on Geoscience and Remote Sensing (TGRS), vol. 57, no. 2, pp. 1205-1218, 2019. (SCI Q1 Top, IF=5.855, ESI Highly Cited Paper) [PDF] [Code] [Dataset] [BibTeX] [Citations: 100+]

[4] Q. Zhang, F. Sun, Q. Yuan, and L. Zhang, “Thick cloud removal for Sentinel-2 time-series images via combining deep prior and low-rank tensor completion,” Proceeding of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), in Brussels, Belgium, 2021. (EI, Oral) [Slides]

[3] Q. Zhang, F. Sun, Q. Yuan, J. Li, H. Shen, and L. Zhang, “Combined the data-driven with model-driven stragegy: A novel framework for mixed noise removal in hyperspectral image,” Proceeding of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), in Hawaii, USA, 2020. (EI, Oral) [Slides]

[2] Q. Zhang, Q. Yuan, J. Li, H. Shen, and L. Zhang, “Cloud and shadow removal for Sentinel-2 by progressively spatiotemporal patch group learning,” Proceeding of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), in Yakohama, Japan, 2019. (EI, Oral) [Slides]

[1] Q. Zhang, Q. Yuan, H. Shen, and L. Zhang, “A unified spatial-temporal-spectral learning framework for reconstructing missing data in remote sensing images,” Proceeding of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), in Valencia, Spain, 2018. (EI, Poster) [Slides]

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