黄绍广  

博士生导师

性别:男

学历:博士研究生毕业

学位:工学博士学位

在职信息:在岗

所在单位:智能科学与技术系

入职时间:2022-10-01

   

个人简介

黄绍广,博士,中国地质大学(武汉)教授,博士生导师,湖北省“百人计划”青年学者,“地大学者”学科骨干人才,CSIG遥感图像专业委员会委员,中国地理信息产业协会委员,国际电气电子学会会员,中国自动化协会会员。2019年获比利时Ghent University工学博士学位,2019-2022年在比利时Ghent University通信与信息处理系从事博士后研究。长期从事高维信号处理、高光谱遥感影像处理、机器学习等方面的研究。主持比利时BOF、国家自然科学基金、中国博士后面上、“地大学者”人才计划等科研项目。目前在国际学术期刊和学术会议发表论文50余篇,ESI高被引论文2篇,获批美国发明专利1项、国家发明专利2项、软件著作权1项。获山东省优秀科研成果奖一等奖、自然资源科技进步奖一等奖、湖北省教学成果奖二等奖、全国高校GIS教学成果奖一等奖、根特大学BOF特别资助奖等多项荣誉奖励。担任国际期刊Remote Sensing 青年编委、《地质科技通报》(中文核心)青年编委、Remote Sensing Lead Guest Editor,担任NIPs、AAAI、ICLR、ICML、ACM MM、ICCV、IEEE TIP、IEEE TNNLS、IEEE TCYB等70多个国际期刊和会议审稿人。


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招收计算机、人工智能、遥感、测绘、图像处理等相关背景博士研究生、硕士研究生(推免和统考),欢迎联系!


代表性学术论文

• T. Luo, Y. Liu, Y. Xu, R. Liu, X. Wang, H. Zeng, S. Huang* and H. Zhang, “Stroke-Based Perception: Discover Novel Oracle Characters”, IEEE Transactions on Multimedia, in press, 2026.

• S. Huang, Y. Wang, H. Zeng*, H. Chen and H. Zhang*, "Self-Supervised One-Step Diffusion Refinement for Snapshot Compressive Imaging", in Proc. AAAI, vol. 40, no. 7, pp. 5095-5103, 2026.

• S. Huang, K. Zhao, H. Chen and H. Zhang*, “Heterogeneous Data-based Global-to-Local Cross-domain Few-shot Classification Method of Hyperspectral Image”, IEEE Transactions on Geoscience and Remote Sensing, vol. 63, 2025.

• S. Huang, W. Xiao, H. Chen, S. K. Bejo and H. Zhang*, “Hyperspectral image classification based on a locally enhanced transformer network”, IEEE Transactions on Geoscience and Remote Sensing, vol. 63, 2025.

• H. Zeng, K. Feng, X. Zhao, J. Cao, S. Huang*, H. Luong and W. Philips, “Degradation-noise-aware deep unfolding transformer for hyperspectral image denoising”, IEEE Transactions on Geoscience and Remote Sensing, vol. 63, 2025.

• R. Liu, T. Luo, S. Huang*, Y. Wu, Z. Jiang and H. Zhang, “CrossMatch: Cross-View Matching for Semi-supervised Remote Sensing Image Segmentation”, IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

• H. Zeng, K. Feng, J. Cao, S. Huang, Y. Zhao, H. Luong, J. Aelterman, W. Philips, “Inheriting Bayer’s Legacy: Joint Remosaicing and Denoising for Quad Bayer Image Sensor”, International Journal of Computer Vision, vol. 132, pp. 4992-5013, 2024.

• S. Huang, H. Zeng, H. Chen and H. Zhang*, “Spatial and Cluster Structural Prior Guided Subspace Clustering for Hyperspectral Image”, IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

• S. Huang, H. Zhang*, J. Xue and A. Pizurica, "Heterogeneous regularizations based tensor subspace clustering for hyperspectral band selection", IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 11, pp. 9259 -9273, 2023.

• H. Zeng, S. Huang*, Y. Chen, H. Luong, W. Philips, “All of Low-Rank and Sparse: A Recast Total Variation Approach to Hyperspectral Denoising”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 7357-7373, 2023.

• S. Huang, H. Zhang* and A. Pizurica, "Subspace clustering for hyperspectral images via dictionary learning with adaptive regularization", IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-17, 2022. ESI高被引论文

• S. Huang, H. Zhang* and A. Pizurica, "A structural subspace clustering approach for hyperspectral band selection", IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2022.

• S. Huang, H. Zhang* and A. Pizurica, "Hybrid-hypergraph regularized multiview subspace clustering for hyperspectral images", IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-16, 2022.

• J. Xue, Y. Zhao, S. Huang, W. Liao, J. C. Chan and S. G. Kong, “Multilayer sparsity-based tensor decomposition for low-rank tensor completion”, IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 11, pp. 6916-6930, 2022. ESI高被引论文

• S. Huang*, B. Cornelis, B. Devolder, M. Martens and A. Pizurica, "Multimodal target detection by sparse coding: application to paint loss detection in paintings", IEEE Transactions on Image Processing, vol. 29, pp. 7681-7696, 2020.

• S. Huang*, H. Zhang, and A. Pizurica, “Semisupervised sparse subspace clustering method with a joint sparsity constraint for hyperspectral remote sensing images,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 3, pp. 989–999, 2019.

• S. Huang, L. Tian and Y. Wei*, “A reconfigurable sound wave decomposition filterbank for hearing aids based on nonlinear transformation”, IEEE Transactions on Biomedical Circuits and Systems, vol. 10, no. 2, pp. 487-496, 2016.


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