汪家明

 

 


姓名:汪家明

出生年月19949

学历(学位):研究生(博士)

毕业院校:武汉大学测绘遥感信息工程国家重点实验室

主要研究方向:遥感影像处理、计算机视觉、深度学习等

研究生招收专业:模式识别与智能系统、计算机应用技术、智能科学与技术

联系方式:wjmecho@wit.edu.cn

简介:202212月毕业于武汉大学摄影测量与遥感计专业,获博士学位,主要研究方向为遥感影像处理及深度学习等。在研究生学习期间,参加国家自然科学基金和军民融合项目等项目,获得2022年地理信息科技进步奖特等奖。近年来,共发表论文20余篇(1篇入选ESI高被引论文),其中第一作者或通讯作者在InformationSciencesIEEETransactions on Geoscience and Remote SensingNeural Networks等高水平期刊上发表SCI论文8篇(中科院一区5),授权发明专利2项(包括1项美国专利)。目前担任IEEETIP / IEEE TGRS / IEEE TMM / Neurocomputing / ICIP等国际杂志和会议审稿人。 

 

承担的主要项目

1.古天乐太阳娱乐集团tyc493智能机器人湖北省重点实验室开放基金,K202034,基于高效深度学习网络的遥感图像超分辨率重建,2022/01-2022/12,在研,参与

代表性科研论文

[1] WangJ, Shao Z, Huang X, et al. Deep locallylinear embedding network[J]. Information Sciences, 2022, 614: 416-431.(SCIIF=8.233,中科院一区) 

[2] WangJ, Shao Z, Huang X, et al. Pan-Sharpeningvia Deep Locally Linear Embedding Residual Network[J]. IEEE Transactions onGeoscience and Remote Sensing, 2022, 60: 1-13.(SCIIF=8.125,中科院一区) 

[3] Wang J, Shao Z, Huang X, etal. From artifact removal to super-resolution[J]. IEEE Transactions onGeoscience and Remote Sensing, 2022, 60: 1-15. (SCIIF=8.125,中科院一区)

[4] WangJ, Shao Z, Huang X, et al. Enhanced imageprior for unsupervised remoting sensing super-resolution[J]. Neural Networks,2021, 143: 400-412. (SCIIF=9.657,中科院一区) 

[5] WangJ, Shao Z, Huang X, et al.ADual-Path Fusion Network for Pan-Sharpening.IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 1-14.(SCIIF=8.125,中科院一区) 

[6] Wang J, Shao Z, Huang X, etal. A Deep Unfolding Method forSatellite Super Resolution. IEEE Transactions on Computational Imaging, 2022. (SCIIF=4.708,中科院二区)

[7] Wang J,Shao Z, Huang X, et al. Spatial–temporal pooling for action recognition invideos[J]. Neurocomputing, 2021, 451: 265-278.(SCIIF=5.779,中科院二区)

[8] Shao Z, WangJ, Lu T, et al. Internal and external spatial–temporal constraints forperson reidentification[J]. Journal of Visual Communication and ImageRepresentation, 2021, 80: 103302. (SCIIF=2.887,中科院三区)

[9] ShaoZ, ChengG, Ma J, Wang Z, Wang J and Li D. Real-time and accurate UAV pedestriandetection for social distancing monitoring in COVID-19 pandemic[J]. IEEEtransactions on multimedia, 2021, 24: 2069-2083. (SCIIF=8.182,中科院一区,ESI高被引论文)

[10] Wang J,Shao Z, Huang X, et al.Unsupervised Remoting Sensing Super-Resolution ViaMigration Image Prior, in Proceedings of International Conference on Multimedia& Expo, 2021.(CCF推荐B类国际会议)

[11] Wang J,Shao Z, Huang X, et al.Pan-sharpening via high-pass modification convolution neural network, inProceedings of IEEE International Conference on Image Processing, 2021.(CCF推荐C类国际会议)

[12] ChengG,Shao Z, Wang J, et al. Dual-Branch Multi-Level Feature AggregationNetwork for Pansharpening[J]. IEEE/CAA Journal of AutomaticaSinica, 2022,9(11): 2023-2026. (SCIIF=7.847,中科院一区)

[13] Wang Z,Shao Z, Huang X, Wang J, and Lu T. SSCAN: A Spatial–Spectral CrossAttention Network for Hyperspectral Image Denoising[J]. IEEE Geoscience andRemote Sensing Letters, 2022, 19: 1-5. (SCIIF=5.343,中科院二区)

发明专利:

1.基于残差注意机制时空联合模型的行人重识别方法及装置邵振峰汪家明CN201911417821.42022-05-13, 中国.

2. PedestrianRe-Identification Method Based on Spatiotemporal Joint Model of ResidualAttention Mechanism and DeviceZhenfengShaoJiaming WangUS11468697B22022-10-11, 美国.

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