赵济 - 中国地质大学(武汉)

个人简介

2017年毕业于武汉大学测绘遥感信息工程国家重点实验室，获摄影测量与遥感专业工学博士学位，在德国宇航中心访问交流一年。近几年主持国家自然科学基金青年基金、“地大学者”青年优秀人才项目、测绘遥感信息工程国家重点实验室开放基金、湖北省智能地学信息处理重点实验室开放基金各一项，在RSE、ISPRS、TIP、TGRS等权威期刊发表学术论文30多篇，其中SCI论文26篇，ESI高被引论文1篇、热点论文1篇，获测绘科技进步奖一等奖、地理信息科技进步奖二等奖、2013年IEEE数据融合与分类大赛亚军等，担任IJCV、TGRS、ISPRS、JSTARS、IJRS等期刊审稿员。

研究领域

概率图、深度学习等机器学习算法、遥感图像智能解译、遥感地学应用

近期论文

查看导师最新文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

[1] J. Zhao, S. Tian, C. Geiß, L. Wang, Y. Zhong, and H. Taubenböck, "Spectral-Spatial Classification Integrating Band Selection for Hyperspectral Imagery With Severe Noise Bands," IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 13, pp. 1597-1609, 2020. (SCI, T2) [2] J. Zhao, Y. Zhong, X. Hu, L. Wei, and L. Zhang, "A robust spectral-spatial approach to identifying heterogeneous crops using remote sensing imagery with high spectral and spatial resolutions," Remote Sens. Environ., vol. 239, p. 111605, 2020. (SCI, T1) [3] Y. Zhong, J. Wang, and J. Zhao, "Adaptive conditional random field classification framework based on spatial homogeneity for high-resolution remote sensing imagery," Remote Sens. Lett., vol. 11, pp. 515-524, 2020. (SCI, T3) [4] Y. Zhong, Y. Su, S. Wu, Z. Zheng, J. Zhao, A. Ma, Q. Zhu, R. Ye, X. Li, and P. Pellikka, "Open-source data-driven urban land-use mapping integrating point-line-polygon semantic objects: A case study of Chinese cities," Remote Sens. Environ., vol. 247, p. 111838, 2020. (SCI, T1) [5] Y. Zhong, X. Hu, C. Luo, X. Wang, J. Zhao, and L. Zhang, "WHU-Hi: UAV-borne hyperspdectral with high spatial resolution (H2) benchmark datasets and classifier for precise crop identification based on deep convolutional neural network with CRF," Remote Sens. Environ., vol. 250, p. 112012, 2020. (SCI, T1) [6] S. Wang, Y. Zhong, J. Zhao, X. Wang, and X. Hu, "S 3 CRF: Sparse Spatial-Spectral Conditional Random Field Target Detection Framework for Airborne Hyperspectral Data," IEEE Access, vol. 8, pp. 46917-46930, 2020. (SCI, T3) [7] X. Lu, Y. Zhong, Z. Zheng, J. Zhao, and L. Zhang, "Edge-Reinforced Convolutional Neural Network for Road Detection in Very-High-Resolution Remote Sensing Imagery," Photogrammetric Engineering & Remote Sensing, vol. 86, pp. 153-160, 2020. (SCI, T3) [8] Z. Zheng, Y. Zhong, A. Ma, X. Han, J. Zhao, Y. Liu, and L. Zhang, "HyNet: Hyper-scale object detection network framework for multiple spatial resolution remote sensing imagery," ISPRS J. Photogramm. Remote Sens., vol. 166, pp. 1-14, 2020. (SCI, T1) [9] Y. Dong, L. Krieger, D. Floricioiu, and J. Zhao, "Glacier calving front extraction from TanDEM-X DEM products of the Antarctic Peninsula," in EGU General Assembly Conference Abstracts, 2020. [10] N. Zhao, A. Ma, Y. Zhong, J. Zhao, and L. Cao, "Self-Training Classification Framework with Spatial-Contextual Information for Local Climate Zones," Remote Sens., vol. 11, p. 2828, 2019. (SCI, T2) [11] L. Wei, M. Yu, Y. Zhong, J. Zhao, Y. Liang, and X. Hu, "Spatial–Spectral Fusion Based on Conditional Random Fields for the Fine Classification of Crops in UAV-Borne Hyperspectral Remote Sensing Imagery," Remote Sens., vol. 11, p. 780, 2019. (SCI, T2) [12] X. Lu, Y. Zhong, Z. Zheng, Y. Liu, J. Zhao, A. Ma, and J. Yang, "Multi-scale and multi-task deep learning framework for automatic road extraction," IEEE Trans. Geosci. Remote Sens., vol. 57, pp. 9362-9377, 2019. (SCI, T2) [13] J. Zhao, Y. Zhong, T. Jia, X. Wang, Y. Xu, H. Shu, and L. Zhang, "Spectral-spatial classification of hyperspectral imagery with cooperative game," ISPRS J. Photogramm. Remote Sens., vol. 135, pp. 31-42, 2018. (SCI, T1) [14] Y. Zhong, X. Wang, Y. Xu, S. Wang, T. Jia, X. Hu, J. Zhao, L. Wei, and L. Zhang, "Mini-UAV-Borne Hyperspectral Remote Sensing: From Observation and Processing to Applications," IEEE Geosci. Remote Sens. Mag., vol. 6, pp. 46-62, 2018. (SCI, T2) [15] Y. Zhong, R. Huang, J. Zhao, B. Zhao, and T. Liu, "Aurora image classification based on multi-feature latent dirichlet allocation," Remote Sens., vol. 10, p. 233, 2018. (SCI, T2) [16] P. Lv, Y. Zhong, J. Zhao, and L. Zhang, "Unsupervised Change Detection Based on Hybrid Conditional Random Field Model for High Spatial Resolution Remote Sensing Imagery," IEEE Trans. Geosci. Remote Sens., vol. 56, pp. 4002-4015, 2018. (SCI, T2) [17] Y. Dong, B. Liu, L. Zhang, M. Liao, and J. Zhao, "Fusion of Multi-Baseline and Multi-Orbit InSAR DEMs with Terrain Feature-Guided Filter," Remote Sens., vol. 10, 2018. (SCI, T2) [18] J. Zhao, Y. Zhong, H. Shu, and L. Zhang, "High-Resolution Image Classification Integrating Spectral-Spatial-Location Cues by Conditional Random Fields," IEEE Trans. Image Process., vol. 25, pp. 4033-4045, Sept. 2016. (SCI, T2) [19] J. Zhao, Y. Zhong, Y. Wu, L. Zhang, and H. Shu, "Sub-Pixel Mapping Based on Conditional Random Fields for Hyperspectral Remote Sensing Imagery," IEEE J. Sel. Topics Signal Process., vol. 9, pp. 1049-1060, Sept. 2015. (SCI, T2) [20] J. Zhao, Y. Zhong, and L. Zhang, "Detail-Preserving Smoothing Classifier Based on Conditional Random Fields for High Spatial Resolution Remote Sensing Imagery," IEEE Trans. Geosci. Remote Sens., vol. 53, pp. 2440-2452, May 2015. (SCI, T2)