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简介

苏鑫，博士，人工智能学院副教授，硕/博研究生导师。2015年法国巴黎高科国立高等电信学院（Telecom ParisTech）信号与图像处理专业获得博士学位,2015-2018年法国国家信息与自动化研究所（INRIA）博士后研究员。主要从事时序影像智能分析，时空智能目标识别，时空遥感大模型等方面研究。主持和参与多项国家自然科学基金、重点研发计划、国防科研等项目，发表多篇Information Fusion、IEEE TIP、IEEE TGRS、ISPRS、JAG等领域TOP期刊。

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招生信息

长期招收人工智能、计算机、电子信息、测绘遥感等方向的硕/博研究生，请联系xinsu.rs@whu.edu.cn。

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主要在研项目【详情】

• 1. 长时序遥感影像的地物分类制图与动态更新方法研究，国家自然科学基金项目-面上，50万，主持

• 2. 道路设施损毁智能侦测系统及预警装置研发-专题四，重点研发子课题，60万，主持

• 3. 视频遥感信息处理的理论及其典型地学应用,国家自然科学基金项目-重点，参与2/7

• 4. 无人机高清摄像裂缝智能识别及可视化系统软件开发，普通横向，69万，主持

• 5. XXXX研究项目，国防横向，75万，主持

• 6. XXXX模块，国防横向，参与2/7

• 7. XXXX软件，国防横向，参与2/7

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近期代表论文【详情】

• -. Expediting Building Footprint Segmentation from High-resolution Remote Sensing Images via progressive lenient supervision

      H Guo, B Du, C Wu, X Su, L Zhang, arXiv preprint arXiv:2307.12220

• SITSMamba for Crop Classification based on Satellite Image Time Series

      X Qin, X Su, L Zhang, arXiv preprint arXiv:2409.09673

  
  

• Urban region function classification via fusing optical imagery and social media data: A spatio-temporal Transformer interaction approach

      Ruiyang Sun, Xin Su*, Qiangqiang Yuan, Hongzan Jiao, Jiang He, Li Zheng, Information Fusion
  

• Spatiotemporal masked pre-training for advancing crop mapping on satellite image time series with limited labels

      X Qin, H Guo, X Su*, Z Zhao, D Wang, L Zhang, JAG

• Hyperspectral Image Denoising Based on Hyper-Laplacian Total Variation in Spectral Gradient Domain

      F Yang, Q Hu, X Su*, IEEE TGRS

• MTCSAR: Fusing Multi-Temporal Interaction with Coherence Prior for SAR Image Denoising

      J Liu, X Su*, Y Xiao, J Li, Q Yuan, IEEE TGRS

• PHTrack: Prompting for Hyperspectral Video Tracking
  

      Y Chen, Y Tang, X Su*, J Li*, Y Xiao, J He, Q Yuan, IEEE TGRS

• Building-Road Collaborative Extraction From Remote Sensing Images via Cross-Task and Cross-Scale Interaction

      H Guo, X Su*, C Wu, B Du, L Zhang, IEEE TGRS

• PCDASNet: Position-Constrained Differential Attention Siamese Network for Building Damage Assessment

      J Wang, H Guo, X Su*, L Zheng, Q Yuan, IEEE TGRS

• SAAN: Similarity-aware attention flow network for change detection with VHR remote sensing images

      H Guo, X Su*, C Wu*, B Du, L Zhang, IEEE TIP

• Statistic Ratio Attention Guided Siamese U-Net for SAR Image Semantic Change Detection

      S Chen, X Su*, L Zheng, Q Yuan, IEEE GRSL

• Decoupling semantic and edge representations for building footprint extraction from remote sensing images

      H Guo, X Su*, C Wu, B Du, L Zhang, IEEE TGRS

• Fast hyperspectral image denoising and destriping method based on graph Laplacian regularization

      X Su, Z Zhang, F Yang, IEEE TGRS

• A coarse-to-fine boundary refinement network for building footprint extraction from remote sensing imagery

      H Guo, B Du, L Zhang, X Su, ISPRS
  

• Inundation impact on croplands of 2020 flood event in three Provinces of China

      X Qin, Q Shi, D Wang, X Su, IEEE JSTARS

• Deep image interpolation: A unified unsupervised framework for pansharpening

      J Gao, J Li, X Su, M Jiang, Q Yuan, Proceedings of the IEEE/CVF Conference on CVPRW

• Multivehicle object tracking in satellite video enhanced by slow features and motion features

        J Wu, X Su*, Q Yuan, H Shen, L Zhang, IEEE TGRS 【Code Download】

• Satellite video super-resolution via multiscale deformable convolution alignment and temporal grouping projection

        Y Xiao, X Su*, Q Yuan, D Liu, H Shen, L Zhang, IEEE TGRS

  CFCANet: A complete frequency channel attention network for SAR image scene classification

        B Su, J Liu, X Su*, B Luo, Q Wang, IEEE JSTARS

• Spatial–temporal gray-level co-occurrence aware CNN for SAR image change detection

        X Zhang, X Su*, Q Yuan, Q Wang, IEEE GRSL

• Scale-robust deep-supervision network for mapping building footprints from high-resolution remote sensing images

        H Guo, X Su*, S Tang, B Du, L Zhang, IEEE JSTARS

• Boundary-aware dual-stream network for VHR remote sensing images semantic segmentation

        Z Nong, X Su*, Y Liu, Z Zhan, Q Yuan, IEEE JSTARS

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