何鸿杰 |
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10 访问 |
个人资料
教育经历2012年9 月-2016年6 月 中国石油大学（华东） 测绘工程 本科 2016年9 月-2019年6 月 兰州大学 地图学与地理信息系统 硕士 2019年9 月-2023年10月 加拿大滑铁卢大学 地理学（遥感影像智能解译） 博士 工作经历2023年11月-2026年2月 加拿大滑铁卢大学 博士后 2026年3月-至今 华东师范大学 副教授 个人简介主要研究方向为遥感影像智能解译与地理空间智能分析。在 International Journal of Applied Earth Observation and Geoinformation、IEEE Transactions on Geoscience and Remote Sensing、Photogrammetric Engineering & Remote Sensing 等国际期刊发表第一作者/通讯作者论文12篇，Google Scholar 引用1000余次。长期参与国际学术服务，担任 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)、International Society for Photogrammetry and Remote Sensing (ISPRS) Congress 及 International Cartographic Conference (ICC) 等重要国际学术会议分会场主席，持续为地球科学与遥感领域的国际学术交流与同行评审工作提供组织与专业支持。同时长期担任多本遥感与计算机视觉领域国际期刊审稿人，为 ISPRS Journal of Photogrammetry and Remote Sensing (ISPRS JPRS)、International Journal of Applied Earth Observation and Geoinformation (JAG)、IEEE Transactions on Geoscience and Remote Sensing (TGRS)、IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)、IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS)、IEEE Transactions on Instrumentation and Measurement (TIM)、IEEE Transactions on Image Processing (TIP)、IEEE Transactions on Intelligent Transportation Systems (TITS) 以及 International Journal of Digital Earth (IJDE) 等国际期刊提供同行评审服务。 社会兼职研究方向基于深度学习的遥感数据超分辨率重建与多源融合技术研究 基于深度学习的建筑物屋顶轮廓线提取 基于深度学习的资源环境遥感监测应用研究 招生与培养欢迎对遥感影像智能解译和地理空间人工智能（GeoAI）方向感兴趣的本科生、硕士生和博士生加入团队。 一、研究方向本团队主要围绕遥感影像智能解译与地理空间智能分析开展研究，重点关注以下方向：
二、培养方式团队注重理论研究与工程应用结合，为学生提供系统的科研训练：
三、学生要求欢迎具有以下背景的学生申请加入：
具备以下基础者优先：
四、团队优势
开授课程科研项目学术成果第一作者/通讯文章： He, H., Ma, L.*, & Li, J.*, 2024. HigherNet-DST: Higher-resolution network with dynamic scale training for rooftop delineation. IEEE Transactions on Geoscience and Remote Sensing, 62, 1-15. DOI: 10.1109/TGRS.2024.3362601. Li, L., He, H.*, Chen, N., Kang, X., & Wang, B., 2024.SLRCNN: Integrating sparse and low-rank with a CNN denoiser for hyperspectral and multispectral image fusion. International Journal of Applied Earth Observation and Geoinformation, 134, 104227. Zhou, H., He, H.*, Xu, L., Ma, L., Zhang, D., Chen, N., Chapman, A. M., & Li, J.*, 2025.A comparative study of deep learning methods for automated road network extraction from high-spatial-resolution remotely sensed imagery. Photogrammetric Engineering & Remote Sensing, 91(3), 163-174. He, H., Xu, L., Chapman, M. A., Ma, L.*, & Li, J.*, 2025. Cost-Effective High-Definition Building Mapping: Box-Supervised Rooftop Delineation Using High-Resolution Remote Sensing Imagery. Photogrammetric Engineering & Remote Sensing, 91(4), 225-239. Gao, K., Lu, D., Li, L., Chen, N., He, H.*, Du, J., Xu L.*, & Li, J., 2025.Instructor–Worker large language model system for policy recommendation: A case study on air quality analysis of the January 2025 Los Angeles wildfires. International Journal of Applied Earth Observation and Geoinformation, 143, 104774. Fan, D., Yang, X., He, H.*, He, H.*, & Fu, B., 2025. Bridging the cloud gap: AHI/ATMS synergy through CNN feature fusion for all-weather SST retrieval. International Journal of Applied Earth Observation and Geoinformation, 144, 104887. Liu, W., Zhong, Y., Zhao, S., Luo, S., Yu, Y., Zhong, X., Tan, W., Guan, H., He, H.*, & Li, J. (2026). DEM super-resolution guided by high-resolution remote sensing images using multitask learning. International Journal of Applied Earth Observation and Geoinformation, 146, 105099. Fatholahi, S., Yin, S., Hu, K., He, H.*, Yao, K. Y., Zhang, D., Lu, D., & Li, J.* (2026). Comparative Evaluation of Deep-Learning Models for Point Cloud Upsampling: Insights from Indoor Parking Lot Data Set. Photogrammetric Engineering & Remote Sensing.DOI: 10.14358/PERS.25-00083R3. Xu, H., He, H.*, Zhang, Y., Zhang, D., & Li, J.* (2026). Semantic Change Detection with Constrained Dual-Head Convolutional Neural Network Architecture for Oil/Gas Well Site Monitoring. Photogrammetric Engineering & Remote Sensing. DOI: 10.14358/PERS.25-00112R3. He, H., Xu, H., Zhang, Y., Gao, K., Li, H., Ma, L.*, & Li, J.* (2022). Mask R-CNN based automated identification and extraction of oil well sites. International Journal of Applied Earth Observation and Geoinformation, 112, 102875. He, H., Gao, K., Tan, W., Wang, L., Chen, N., Ma, L.*, & Li, J.* (2022). Super-resolving and composing building dataset using a momentum spatial-channel attention residual feature aggregation network. International Journal of Applied Earth Observation and Geoinformation, 111, 102826. He, H., Jiang, Z., Gao, K., Narges Fatholahi, S., Tan, W., Hu, B., Xu, H., Chapman, A. M.,& Li, J. (2022). Waterloo building dataset: A city-scale vector building dataset for mapping building footprints using aerial orthoimagery. Geomatica, 75(3), 99-115. He, H., Yang, K., Wang, S., Petrosians, H. A., Liu, M., Li, J., Junior, J. M., Gonçalves, W. N., Wang, L., & Li, J. (2021). Deep learning approaches to spatial downscaling of GRACE terrestrial water storage products using EALCO model over Canada. Canadian Journal of Remote Sensing, 47(4), 657-675. 专利成果 [1] 李军，何鸿杰，何直蒙，马凌飞，李静，李志龙，赵花（2025）. 一种基于深度学习的自动纠错方法，发明专利授权号: ZL202310948751.5 [2] 李军，何鸿杰，蔡雨薇，马凌飞，李静，郭俊跃（2025）. 一种基于高分辨率遥感影像的建筑物边界自动提取方法，发明专利授权号: ZL202310908022.7 荣誉及奖励 |