研究领域
基于空天陆海多平台、多模态数据的全球多尺度时空信息重构与预测——应用领域海洋亚中尺度过程监测、实景三维中国建设、数字孪生、灾害监测与评估、智慧农业等。具体研究方向和核心技术如下：
1 面向多源遥感图像/视频/点云的时空信息提取技术
语义分割、实例分割、超分辨率、物理神经网络
2 基于多时相、多模态数据的时变信息关联与分析技术
多维度变化检测、跨模态信息关联、目标重识别/地理地位、视觉-语言模型
3 基于超广义立体像对的时空信息重构技术
三维重建、神经渲染、数字地球
4 基于NVIDIA与国产平台的上述智能算法的嵌入式部署
论文成果
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Gao, FJ,Yan, YM,Lin, HM,Shi, R PIIE-DSA-Net for 3D Semantic Segmentation of Urban Indoor and Outdoor Datasets:REMOTE SENSING,2022,15
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Yan, YM,Zhou, WK,Su, N,Zhang, UniRender: Reconstructing 3D Surfaces from Aerial Images with a Unified Rendering Scheme:REMOTE SENSING,2023,18
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Zhao, CH,Zhang, C,Yan, YM,Su, A 3D Reconstruction Framework of Buildings Using Single Off-Nadir Satellite Image:REMOTE SENSING,2021,21
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Yan, YM,Tan, ZC,Su, N A Data Augmentation Strategy Based on Simulated Samples for Ship Detection in RGB Remote Sensing Images:ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2019,6
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Yan, YM,Wang, WX,Su, N,Wang, Z Cross-Dimensional Object-Level Matching Method for Buildings in Airborne Optical Image and LiDAR Point Cloud:IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2022
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Yan, YM,Wang, ZL,Xu, CG,Su, N GEOP-Net: Shape Reconstruction of Buildings From LiDAR Point Clouds:IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2023
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Zhao, CH,Zhang, C,Yan, YM,Su, Shape Reconstruction of Object-Level Building From Single Image Based on Implicit Representation Network:IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2022
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Zhao, CH,Wang, WX,Yan, YM,Su, A Novel Object-Level Building-Matching Method across 2D Images and 3D Point Clouds Based on the Signed Distance Descriptor (SDD):REMOTE SENSING,2023,12
专利
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著作成果
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