陈雨时
发布日期：2024-05-10 浏览次数：次
基本信息 教学科研 出版物 English Version 新建主栏目 个人简介 名称 陈雨时（Yushi Chen），工学博士，长聘教授，博士生导师。 从事人工智能（深度学习）理论及应用、遥感数据分析及处理、雷达信号智能处理、智慧农业、医学图像智能诊断等领域的研究。 发表学术论文70余篇，SCI收录50余篇（入选ESI高被引论文15篇、ESI热点论文4篇、IEEE地学遥感协会最高影响力论文3篇、Remote Sensing最佳论文1篇），SCI引用6,000余次，Google引用11,000余次，入选科睿唯安全球高被引科学家、爱思唯尔中国高被引学者。 主持国家自然科学基金（面上3项、青年1项）、国家博士后面上基金、国家重点实验室开放基金、校科研创新基金、民口横向等多项科研项目；作为核心成员参与多项科研项目。 获得黑龙江省科学技术奖一等奖1项（第2完成人）、二等奖1项，黑龙江省高等教育教学成果奖二等奖1项。 指导多名学生获得哈尔滨工业大学金/银牌毕业生、优秀硕士论文、优秀本科设计（论文）。 文章及代码下载： https://www.researchgate.net/profile/Yushi_Chen https://github.com/YushiChen 荣誉奖励 名称 2024年：IEEE GRSS 2024 Highest Impact Paper Award； 2023年：科睿唯安（Clarivate Analytics）全球高被引科学家（Highly Cited Researchers）； 2023年：爱思唯尔（Elsevier）中国高被引学者（Highly Cited Chinese Researchers）； 2023年：Remote Sensing 2023 Best Paper Awards； 2023年：哈尔滨工业大学 优秀硕士论文 指导教师； 2023年：哈尔滨工业大学 优秀博士论文提名论文 指导教师； 2023年：斯坦福 全球前2%顶尖科学家（“生涯影响力”榜单及“年度影响力”榜单）； 2022年：爱思唯尔（Elsevier）中国高被引学者（Highly Cited Chinese Researchers）； 2022年：哈尔滨工业大学 优秀硕士论文 指导教师； 2022年：斯坦福 全球前2%顶尖科学家（“年度影响力”榜单）； 2022年：入选全球学者学术影响力排行榜； 2022年：哈尔滨工业大学 电信学院 学术新星奖； 2021年：爱思唯尔（Elsevier）中国高被引学者（Highly Cited Chinese Researchers）； 2021年：哈尔滨工业大学 优秀硕士论文 指导教师； 2021年：哈尔滨工业大学 本科生优秀毕业设计（论文）)指导教师； 2020年：黑龙江省 高等教育教学成果奖二等奖； 2020年：爱思唯尔（Elsevier）中国高被引学者（Highly Cited Chinese Researchers）; 2020年：IEEE GRSS 2020 Highest Impact Paper Award; 2020年：哈尔滨工业大学 优秀硕士论文 指导教师； 2019年：IEEE GRSS 2019 Highest Impact Paper Award； 2019年：哈尔滨工业大学 研究生教育成果一等奖； 2019年：哈尔滨工业大学 金牌硕士毕业生 指导教师； 2018年：黑龙江省科学技术奖一等奖（自然科学类）； 2017年：IEEE TGRS Top 15 reviewers； 2017年：哈尔滨工业大学 银牌硕士毕业生 指导教师； 2015年：哈尔滨工业大学 金牌硕士毕业生 指导教师； 2014年：哈尔滨工业大学 金牌硕士毕业生 指导教师； 2013年：哈尔滨工业大学 青年教师教学基本功大赛二等奖； 2009年：黑龙江省 高校科学技术奖二等奖； 2009年：黑龙江省 科学技术奖二等奖（自然科学类）。 学术任职 名称 国家自然科学基金 评议人； 遥感技术与应用 青年编委； 全国研究生教育评估监测专家库专家； 电子电器工程师协会(IEEE)会员； 地球科学与遥感协会 会员； 担任以下国内、国际期刊、会议审稿人： IEEE Transactions on Geoscience and Remote Sensing (TGRS); Remote Sensing of Environment (RSE); IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS); IEEE Geoscience and Remote Sensing Letters (GRSL); International Journal of Remote Sensing (IJRS); Remote Sensing Letters (RSL); IEEE Transactions on Multimedia (TMM); Information Sciences; Pattern Recognition Letters; ISPRS Journal of Photogrammetry and Remote Sensing; Multimedia Tools and Applications; Remote Sensing; IEEE Access; 厦门大学学报(自版)；IEEE Transactions on Cybernetics; Information Fusion; Journal of Experimental & Theoretical Artificial Intelligence; International Geoscience And Remote Sensing Symposium (IGARSS) 2017,2018, 2019; WIREs Data Mining and Knowledge Discovery; Advancement in Science and Technology Research; IEEE Transactions on Image Processing (TIP); IEEE Signal Processing Letters; Journal of King Saud University - Computer and Information Sciences; International Journal of Digital Earth; PLOS ONE; Neurocomputing; Journal of Photogrammetry, Remote Sensing and Geoinformation Science 教育、工作经历 名称 2008.03 - 今 哈尔滨工业大学，教师 2008.12 - 2012.05 北京市遥感信息研究所，博士后 1997.09 - 2001.07 哈尔滨工业大学 电子信息工程 工学学士 2001.09 - 2003.07 哈尔滨工业大学 信号与信息处理 工学硕士 2003.09 - 2008.01 哈尔滨工业大学 信息与通信工程 工学博士 研究生培养 名称 每年招收1-2名博士生、2-6名硕士生，2名本科毕设。 具有良好的专业知识、编程能力、英文写作者优先，有意者请提前联系。 李阔 (Kuo Li, 2023-M19) 杨博涵 (Bohan Yang, 2023-M18) 张玉帛 (Yubo Zhang, 2023-D05) 杜云涛 (Yuntao Du, 2022-M17, 2024--D06) 曾颖 (Ying Zeng, 2022-M16) 黄凌博 (Lingbo Huang, 2022-D04) 张梦璐 (Menglu Zhang, 2021-D03) 王珺玮 (Junwei Wang, 2021-M15) 王伟权 (Weiquan Wang, 2021-M14)，2022 国家奖学金获得者，2023 哈尔滨工业大学 校优秀毕业生，2023 哈尔滨工业大学 优秀硕士论文 李青云 (Qingyun Li, 2021-D02)，2021 本科生优秀毕业设计(论文), 2022 哈尔滨工业大学深交所 奖学金 黄凌博 (Lingbo Huang, 2020-M13)，2021 国家奖学金获得者，2022 哈尔滨工业大学 优秀硕士论文 谢浩 (Hao Xie, 2019-M12), 2021 哈尔滨工业大学 优秀硕士论文，2021 哈尔滨工业大学 校优秀毕业生 张浩宇 (Haoyu Zhang, 2019-M11) 何欣 (Xin He, 2019-D01), 2020 哈尔滨工业大学深交所 奖学金，2021 国家奖学金获得者，2021 哈尔滨工业大学 春雁英才计划入选者，2023 哈尔滨工业大学 校优秀毕业生，2023 哈尔滨工业大学 优秀博士论文提名论文 邵广庆 (Guangqing Shao, 2018-M10)，2020 哈尔滨工业大学 优秀硕士论文 代广喆 (Guangzhe Dai, 2018-M09) 朱凯强 (Kaiqiang Zhu, 2017-M08)，毕设成绩：优秀 祝琳 (Lin Zhu, 2017-M07)，2019 哈尔滨工业大学 金牌毕业生，2019 校优秀毕业生，2018 国家奖学金获得者 张悦 (Yue Zhang, 2016-M06) 李春阳 (Chunyang Li, 2015-M05)，2017 哈尔滨工业大学 银牌毕业生 马顺利 (Shunli Ma, 2015-M04) 姜含露 (Hanlu Jiang, 2014-M03)，毕设成绩：优秀 赵兴 (Xing Zhao, 2013-M02)，2015 哈尔滨工业大学 金牌毕业生，2015 黑龙江省三好学生，2015 校优秀毕业生，2014 国家奖学金获得者 林洲汉 (Zhouhan Lin, 2012-M01)，2014哈尔滨工业大学 金牌毕业生 本科生培养 名称 2024: 王昕怡(Xinyi Wang, 2024-B38), 金督程(Ducheng Jin, 2024-B39) 2023: 骆赜语(Zeyu Luo, 2023-B34), 杨博涵(Bohan Yang, 2023-B35), 李阔(Kuo Li, 2023-B36), 李永峰(Yongfeng Li, 2023-B37) 2022: 赵子皓(Zihao Zhao, 2022-B31), 苗宇航(Yuhang Miao, 2022-B32), 董昊炎(Haoyan Dong, 2022-B33)，2022哈尔滨工业大学 校优秀毕业生 2021: 李青云(Qingyun Li, 2021-B29,本科生优秀毕业设计(论文))，王伟权(Weiquan Wang, 2021-B30) 2020: 刘贺(He Liu, 2020-B26),罗淮文(Huaiwen Luo, 2020-B27), 任德锋(Defeng Ren, 2019-B28) 2019: 黄凌博(Lingbo Huang, 2019-B23),谢浩(Hao Xie, 2019-B24),安昶帆(Changfan An, 2019-B25) 2018: 王子南(Zinan Wang, 2018-B21),赵达(Da Zhao, 2018-B22) 2017: 曹浩天(Haotian Cao, 2017-B18),朱凯强(Kaiqiang Zhu, 2017-B19),石凡(Fan Shi, 2017-B20) 2016: 贾金让(Jingrang Jia, 2016-B16),郭俊洋(Junyang Guo, 2016-B17) 2015: 马顺利(Shunli Ma, 2015-B13),李德皋(DeGao Li, 2015-B14),郭峻凌(Junling Guo, 2015-B15) 2014: 姜含露(Hanlu Jiang, 2014-B10),高超(Chao Gao, 2014-B11),关宜青(Yiqing Guan, 2014-B12) 2013: 郑小聪(Xiaochong Zheng, 2013-B08),闫加明(Jiaming Yan, 2013-B09) 2012: 李达(Da Li, 2012-B05),刘家龙(Jialong Liu, 2012-B06),曲昌博(Changbo Qu, 2012-B07) 2011: 谢佳君(JiajunXie, 2011-B03),刘良庆(Liangqing Liu, 2011-B04) 2010: 李克来(Kelai Li, 2010-B02) 2009: 孙婉婷(Wanting Sun, 2009-B01) 研究领域 名称 主要研究方向为：遥感数据分析及处理；医学图像智能诊断；机器学习理论及应用，重点体现在: 高光谱遥感数据特征提取及分类。设计并实现了高光谱遥感数据的第一个具有深度结构的模型(堆栈自动编码机，SAE，2014)，开辟了高光谱遥感数据特征提取及分类的新方向；在此基础上，提出空谱深度信念网(SS-DBN， 2015)、3D卷积神经网络(3D-CNN，2016)、生成式对抗网络(3D-GAN，2018)、深度卷积胶囊网络(Conv-Capsule， 2019)、自动化设计深度模型(3D-Auto-CNN，2019)、深度模型集成(DL-Ensemble，2019)等用于高光谱数据的处理，推动了深度学习在高光谱遥感领域的应用。 激光雷达(LiDAR)数据分析及处理。提出基于深度卷积神经网络的LiDAR数据特征提取方法，实现LiDAR数据 的像素级分类。 多源遥感数据融合。针对高/多光谱、LiDAR数据的融合，设计并实现了第一个具有深度结构的融合模型(该模型应用卷积神经网络进行特征提取，应用深度神经网络进行特征融合)，开辟了多源遥感数据融合的新方向。 医学图像智能诊断。针对新型PET/CT医学影像，综合应用机器学习技术，让计算机学习和模仿医生阅片、诊 断，实现疾病的早发现、早诊断，降低误诊、漏诊概率。 深度学习理论及应用。作为机器学习的一个新领域，深度学习的动机在于建立、模拟人脑进行分析学习的神经网络，用来解释图像、语音和文本等数据，近年来在学术界和工业界取得了广泛关注。 主讲课程 名称 光学与红外遥感 神经网络理论与应用 天空之眼-现代遥感技术(文化素质选修课) 信号与系统(专业基础课，考研课程) 卫星定位导航(双语课程) 出版物2024 名称 文章及代码下载：https://www.researchgate.net/profile/Yushi_Chen Xin He, Yushi Chen*, Lingbo Huang, Danfeng Hong, Qian Du, Foundation Model-based Multimodal Remote Sensing Data Classification, IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024. (SCI, IF: 8.2) Qingyun Li, Yushi Chen*, Xin He, Lingbo Huang, Co-training Transformer for Remote Sensing Image Classification, Segmentation and Detection, IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024. (SCI, IF: 8.2) Xing Zeng, Yushi Chen*, Xue Yang, Qingyun Li, Junchi Yan, ARS-DETR: Aspect Ratio Sensitive Detection Transformer for Aerial Oriented Object Detection, IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024. (SCI, IF: 8.2) 出版物2023 名称 Lingbo Huang, Yushi Chen*, Xin He, Spectral-Spatial Masked Transformer with Supervised and Contrastive Learning for Hyperspectral Image Classification, IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023. (SCI, IF: 8.2) Xin He, Yushi Chen*, Lingbo Huang, Bayesian Deep Learning for Hyperspectral Image Classification with Low Uncertainty, IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023. (SCI, IF: 8.2) Menglu Zhang, Lei Yu, Yushi Chen*, Ye Zhang, Enhanced Transformers for Radar Jamming Recognition, International Radar Conference 2023 Zhaokui Li, Hui Guo, Yushi Chen, Cuiwei Liu, Qian Du, Zhuoqun Fang, Few-shot Hyperspectral Image Classification with Self-supervised Learning, IEEE Transactions on Geoscience and Remote Sensing, in press, 2023. (SCI, IF: 8.2) 出版物2022 名称 Xin He, Yushi Chen*, Pedram Ghamisi, Dual Graph Convolutional Network for Hyperspectral Image Classification with Limited Training Samples, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022. (SCI, IF: 8.125, ESI高被引论文) Xin He, Yushi Chen*, Lingbo Huang, Toward a Trustworthy Classifier with Deep CNN: Uncertainty Estimation Meets Hyperspectral Image, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.(SCl, IF: 8.125) Weiquan Wang, Yushi Chen*, Pedram Ghamisi, Transferring CNN with Adaptive Learning for Remote Sensing Scene Classification, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022. (SCI, IF: 8.125, ESI高被引论文) Qingyun Li, Yushi Chen*, Ying Zeng, Transformer with Transfer CNN for Remote-Sensing-Image Object Detection, Remote Sensing, 2022,14(4),984. (SCI, IF: 5.349, ESI高被引论文) Lingbo Huang, Yushi Chen*, Xin He and Pedram Ghamisi, Supervised Contrastive Learning-Based Classification for Hyperspectral Image, Remote Sensing, 2022,14(21),5530. (SCI, IF: 5.349) Xin He, Yushi Chen*, Qingyun Li, Two-Branch Pure Transformer for Hyperspectral Image Classification, IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022. (SCI, IF: 5.343) Weiquan Wang, Yushi Chen*, Xin He, Zhaokui Li, Soft Augmentation-Based Siamese CNN for Hyperspectral Image Classification With Limited Training Samples, IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022. (SCI, IF: 5.343) Qingyun Li, Yushi Chen*, Pedram Ghamisi, Complementary Learning-Based Scene Classification of Remote Sensing Images with Noisy Labels, IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022. (SCI, IF: 5.343) Zihao Zhao, Yushi Chen*, Xin He, Adaptively heterogeneous transfer learning for hyperspectral image classification, Remote Sensing Letters, 2022, 13(12). (SCI, IF: 2.369) Zhaokui Li, Ming Liu, Yushi Chen, Yimin Xu, Wei Li, Qian Du, Deep Cross-Domain Few-Shot Learning for Hyperspectral Image Classification, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 202 2. (SCI, IF: 8.125, ESI高被引论文) Zhuoqun Fang, Yuexin Yang, Zhaokui Li, Wei Li, Yushi Chen, Li Ma, Qian Du, Confident Learning-Based Domain Adaptation for Hyperspectral Image Classification, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022. (SCI, IF: 8.125) Yan Wang, Ming Liu, Zhaokui Li, Qian Du, Yushi Chen, Fei Li, and Haibo Yang, Heterogeneous Few-shot Learning for Hyperspectral Image Classification, IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022. (SCI, IF: 5.343) 出版物2021 名称 Xin He, Yushi Chen*, Zhouhan Lin, Spatial-Spectral Transformer for Hyperspectral Image Classification, Remote Sensing, 2021,13(3), 498. (SCI, IF: 4.848, ESI高被引论文, Remote Sensing Best Paper Awards) Xin He, Yushi Chen*, Modifications of the Multi-Layer Perceptron for Hyperspectral Image Classification, Remote Sensing, 2021,13(17), 3547. (SCI, IF: 4.848) Lingbo Huang, Yushi Chen*, Dual-Path Siamese CNN for Hyperspectral Image Classification With Limited Training Samples, IEEE Geoscience and Remote Sensing Letters, Vol. 18, No. 3, 2021, pp: 518-522. (SCl, IF: 3.833) Xin He, Yushi Chen*, Transferring CNN Ensemble for Hyperspectral Image Classification, IEEE Geoscience and Remote Sensing Letters, Vol. 18, No. 5, 2021, pp: 876-880. (SCI, IF: 3.534) Hao Xie, Yushi Chen*, LiDAR Data Classification Based on Automatic designed CNN, IEEE Geoscience and Remote Sensing Letters, Vol. 18, No. 9, 2021, pp: 1665 - 1669. (SCI, IF: 3.833) Hao Xie, Yushi Chen*, Pedram Ghamisi, Remote Sensing Image Scene Classification via Label Augmentation and Intra-class Constraint, Remote Sensing, 2021,13(13), 2566. (SCI, IF: 4.848) Lingbo Huang, Yushi Chen*, Xin He, Weakly Supervised Classification of Hyperspectral Image Based on Complementary Learning, Remote Sensing, 2021,13(24), 5009. (SCI, IF: 4.848) Haoyu Zhang, Lei Yu, Yushi Chen*, Yinsheng Wei, Fast Complex-Valued CNN for Radar Jamming Signal Recognition, Remote Sensing, 2021,13(15), 2867. (SCI, IF: 4.848) Haoyu Zhang, Yushi Chen*, Xin He, et al., BOOSTING CNN FOR HYPERSPECTRAL IMAGE CLASSIFICATI ON, International Geoscience And Remote Sensing Symposium (IGARSS) 2021. (El) 出版物2020 名称 Xin He, Yushi Chen*, Pedram Ghamisi, Heterogeneous Transfer Learning for Hyperspectral Image Classi fication Based on Convolutional Neural Network, IEEE Transactions on Geoscience and Remote Sensing, Vol. 58, No. 5, 2020, pp: 3246 - 3263. (SCI, IF: 5.630, ESI高被引论文) Guangqing Shao, Yushi Chen*, Yinsheng Wei, Convolutional neural network-based radar jamming signal classification with sufficient and limited samples, IEEE Access, Vol. 8, pp: 80588-80598. (SCI, IF: 4.098) Guangqing Shao, Yushi Chen*, Yinsheng Wei, Deep Fusion for Radar Jamming Signal Classification Based on CNN, IEEE Access, Vol. 8, pp: 117236-117244. (SCI, IF: 4.098) 出版物2019 名称 Yushi Chen*, Kaiqiang Zhu, Lin Zhu, Xin He, Pedram Ghamisi, Jón Atli Benediktsson, Automatic Design of Convolutional Neural Network for Hyperspectral Image Classification, IEEE Transactions on Geoscience and Remote Sensing, Vol. 57, No. 9, 2019, pp: 7048 - 7066. (SCI, IF: 5.630, ESI高被引论文) Yushi Chen*, Ying Wang, Yanfeng Gu, Pedram Ghamisi, Xiuping Jia, Deep Learning Ensemble for Hyper spectral Image Classification, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 12, No. 6, 2019, pp: 1882- 1897. (SCI, IF: 3.392) Yushi Chen*, Lingbo Huang, Lin Zhu, Naoto Yokoya and Xiuping Jia, Fine-Grained Classification of Hy perspectral Imagery Based on Deep Learning, Remote Sensing, 2019,11 (22), 2690. (SCI, IF: 4.030) Xin He, Yushi Chen*, Optimized Input for CNN-Based Hyperspectral Image Classification Using Spatial Transformer Network, IEEE Geoscience and Remote Sensing Letters, Vol. 16, No. 12, 2019, pp: 1884-1888. (SCI, IF: 3.534) Kaiqiang Zhu, Yushi Chen*, Pedram Ghamisi, Xiuping Jia, Jón Atli Benediktsson, Deep Convolutional Capsule Network for Hyperspectral Image Spectral and Spectral-Spatial Classification, Remote Sensing, 2 019, 11(3), 223. (SCI, IF: 4.030) Aili Wang, Ying Wang, Yushi Chen*, Hyperspectral Image Classification Based on Convolutional Neural Network and Random Forest, Remote Sensing Letters, Vol. 10, No. 11, 2019, pp: 1086-1094. (SCI, IF: 2.0 24) Shutao Li, Weiwei Song, Leyuan Fang, Yushi Chen, Pedram Ghamisi, Jón Atli Benediktsson, Deep Learning for Hyperspectral Image Classification: An Overview, IEEE Transactions on Geoscience and Remote S ensing, Vol. 57, No. 9, 2019, pp: 6690 - 6709. (SCI, IF: 5.630, ESI高被引论文，ESI热点论文) Xin He, Aili Wang, Pedram Ghamisi, Guoyu Li, Yushi Chen*, LiDAR Data Classification Using Spatial Tran sformation and CNN, IEEE Geoscience and Remote Sensing Letters, Vol. 16, No. 1, 2019, pp: 125-129. (S Cl, IF: 3.534) Di Wu, Ye Zhang, Yushi Chen, Shengwei Zhong, Vehicle Detection in High-Resolution Images Using Su perpixel Segmentation and CNN Iteration Strategy, IEEE Geoscience and Remote Sensing Letters, Vol. 1 6, No. 1, 2019, pp: 105-109. (SCI, IF: 3.534) 出版物2018 名称 Lin Zhu, Yushi Chen*, Pedram Ghamisi, and Jón Atli Benediktsson, Generative Adversarial Networks for Hyperspectral Image Classification, IEEE Transactions on Geoscience and Remote Sensing, Vol. 56, No.9, 2018, pp: 5046- 5063. (SCI, IF: 4.662, ESI高被引论文, ESI热点论文) Aili Wang, Xin He, Pedram Ghamisi, and Yushi Chen*, LiDAR Data Classification Using Morphological Pr ofiles and Convolutional Neural Networks, IEEE Geoscience and Remote Sensing Letters, Vol. 15, No. 5, 2018, pp: 774 - 778. (SCI, IF: 2.892) Pedram Ghamisi, Emmanuel Maggiori, Shutao Li, Roberto Souza, Yuliya Tarablaka, Gabriele Moser, Andr ea De Giorgi, Leyuan Fang, Yushi Chen, Mingmin Chi, Sebastiano B. Serpico, Jón Atli Benediktsson, New Frontiers in Spectral-Spatial Hyperspectral Image Classification: The Latest Advances Based on Mathe matical Morphology, Markov Random Fields, Segmentation, Sparse Representation, and Deep Learning, IEEE Geoscience and Remote Sensing Magazine, vo. 6, No. 3, 2018, pp: 10-43. (SCI, IF: 4932, ESI高被 引论文,ESI热点论文) 出版物2017 名称 Yushi Chen*, Lin Zhu, et al., Hyperspectral Images Classification with Gabor Filtering and Convolutional Neural Network, IEEE Geoscience and Remote Sensing Letters, Vol. 14, No. 12, 2017, pp: 2355 - 2359. (SCI, IF: 2.761, ESI高被引论文) Yushi Chen*, Chunyang Li, et al., Deep Fusion of Remote Sensing Data for Accurate Classification, IEEE Geoscience and Remote Sensing Letters, Vol. 14, No. 8, 2017, pp: 1253 - 1257. (SCI, IF: 2.761) Yushi Chen*, Shunli Ma, et al., Hyperspectral Data Clustering Based on Density Analysis Ensemble, Remote Sensing Letters, Vol. 8, No. 2, 2017, pp: 194-203. (SCI, IF: 1.487) Pedram Ghamisi, Javier Plaza, Yushi Chen, Jun Li, Antonio J Plaza, Advanced Spectral Classifiers for Hyperspectral Images: A review, IEEE Geoscience and Remote Sensing Magazine, vo. 5, No. 1, 2017, pp: 8-3 2. (SCI, IF: 2.676, ESI高被引论文) Xi Chen, Gongjian Zhou, Yushi Chen, et al., Supervised Multiview Feature Selection Exploring Homoge neity and Heterogeneity With -Norm and Automatic View Generation, IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 4, 2017, pp: 2074 - 2088. (SCI, IF: 4.942) Shengwei Zhong, Ye Zhang, Yushi Chen, Di Wu, Combining Component Substitution and Multiresoluti on Analysis: A Novel Generalized BDSD Pansharpening Algorithm, IEEE Journal of Selected Topics in Ap plied Earth Observations and Remote Sensing, Vol.10, No.6f 2017, pp: 2867 - 2875. (SCI, IF: 2.913) 出版物2016 名称 Yushi Chen*, Hanlu Jiang, Chunyang Li, Xiuping Jia, Pedram Ghamisi, Deep Feature Extraction and Clas sification of Hyperspectral Images Based on Convolutional Neural Networks, IEEE Transactions on Geos cience and Remote Sensing, Vol. 54, No. 10, 2016, pp: 6232 - 6251. (SCI, IF: 4.942, ESI高被引论文，ESI热点论文, IEEE GRSS Highest Impact Paper) Yushi Chen*, Chunyang Li, et al., DEEP FUSION OF HYPERSPECTRAL AND LIDAR DATA FOR THEMATIC C LASSIFICATION, International Geoscience And Remote Sensing Symposium (IGARSS) 2016. (El) Pedram Ghamisi, Yushi Chen, Xiao Xiang Zhu, A Self-Improving Convolution Neural Network for the Cl assification of Hyperspectral Data, IEEE Geoscience and Remote Sensing Letters, Vol. 13, No. 10, 2016, pp: 1537- 1541. (SCI, IF: 2.228) Xi Chen, Jinzi Qi, Yushi Chen, et al., Adaptive semisupervised feature selection without graph construction for very high resolution remote sensing images, Journal of Applied Remote Sensing, Vol. 10, No. 2, 2016. (SCIJF: 0.937) Zhen Zuo, Bing Shuai, Gang Wang, Xiao Liu, Xingxing Wang, Bing Wang, Yushi Chen, Learning Contextual Dependence With Convolutional Hierarchical Recurrent Neural Networks, IEEE Transactions on Image Processing, Vol. 25, No. 7, 2016, pp: 2983 - 2996. (SCI, IF: 3.735) Yidan Teng, Ye Zhang, Yushi Chen, Chunli Ti, Adaptive Morphological Filtering Method for Structural F usion Restoration of Hyperspectral Images, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 9, No. 2, 2016, pp: 655-667. (SCI, IF: 2.145) 出版物2015 名称 Yushi Chen*, Xing Zhao, Xiuping Jia, Spectral-Spatial Classification of Hyperspectral Data Based on Deep Belief Network, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol.8, No.6, 2015, pp: 2381- 2392. (SCI, IF: 3.026, ESI高被引论文) Ran Wei, Ye Zhang, Yushi Chen. Anisotropy regularization-based restoration of imaging process in line -scanning spectrometer. JOURNAL OF APPLIED REMOTE SENSING, Vol. 9, No. 1, 2015. (SCI, IF: 1.183) Zhen Zuo, Bing Shuai, Gang Wang, Xiao Liu, Xingxing Wang, Bing Wang, and Yushi Chen, Convolutional recurrent neural networks: Learning spatial dependencies for image representation, 2015 IEEE Confere nce on Computer Vision and Pattern Recognition Workshops (CVPRW), pp: 18 - 26 Di Wu, Ye Zhang, Yushi Chen, 3D SPARSE CODING BASED DENOISING OF HYPERSPECTRAL IMAGES, IEEE IGARSS 2015, (El) 张钧萍，谷延锋，陈雨时。遥感数字图像分析导论(第5版，译著)(4-7章),电子工业出版社。 面向高空间分辨率遥感大数据的特征提取方法，中华人民共和国发明专利，专利号201510152162.1 基于卷积神经网络的高光谱遥感数据特征提取方法，中华人民共和国发明专利，专利号201510158325.7 出版物2014 名称 Yushi Chen*, Zhouhan Lin, Xing Zhao, Gang Wang, Yanfeng Gu, Deep Learning-Based Classification of Hyperspectral Data, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol.7, No.6f 2014, pp: 2094 - 2107. (SCI, IF: 2.874, ESI高被引论文，IEEE GRSS Highest Impact Paper) Yushi Chen*, Xing Zhao, Zhouhan Lin, Optimizing Subspace SVM Ensemble for Hyperspectral Imagery Classification, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vbl.7, No.4, 2014, pp: 1295 - 1305. (SCI, IF: 2.874) Yushi Chen*, Xing Zhao, Zhouhan Lin, JOINT ADABOOST AND MULTIFEATURE BASED ENSEMBLE FOR HYPERSPECTRAL IMAGE CLASSIFICATION, International Geoscience And Remote Sensing Symposium (IGARSS) 2014, pp： 2874-2877, Quebec, Canada. (El) Shengwei Zhong, Yushi Chen, Ye Zhang, SPATIAL INFORMATION AIDED FINE CLASSIFICATION OF HYPERSPECTRAL IMAGES WITH SIMILAR SPECTRUMS, International Geoscience And Remote Sensing Symposium (IGARSS) 2014, pp: 2882-2885, Quebec, Canada. (El) Yidan Teng, Ye Zhang, Yushi Chen, A BIDIRECTIONAL GRADIENT PREDICTION BASED METHOD FOR HYPERSPECTRAL DATA JUNK BANDS RESTORATION, International Geoscience And Remote Sensing Symposium (IGARSS) 2014, pp: 4624-4627, Quebec, Canada. (El) Yidan Teng, Ye Zhang, Yushi Chen, Chunli Ti, A NOVEL HYPERSPECTRAL IMAGES DESTRIPING METHOD BASED ON EDGE RECONSTRUCTION AND ADAPTIVE MORPHOLOGICAL OPERATORS, International Conference on Image Processing (ICIP) 2014, pp: 1-5, Paris, France. (El) 陈雨时，高光谱数据降维及压缩技术(专著)，哈尔滨工程大学出版社。 基于集成学习的高光谱遥感数据分类方法，中华人民共和国发明专利，专利号201410283594.1 基于深度学习的高光谱遥感数据分类方法，中华人民共和国发明专利，专利号201410359935.9 基于分层集成学习的高光谱遥感图像分类方法，中华人民共和国发明专利，专利号201410541909.8 出版物2013 名称 Yushi Chen*, Zhouhan Lin, Xing Zhao, RIEMANNIAN MANIFOLD LEARNING BASED k-NEAREST-NEIGHB OR FOR HYPERSPECTRAL IMAGE CLASSIFICATION, International Geoscience And Remote Sensing Symposium (IGARSS) 2013, pp: 1975-1978, Melbourne, Australia. (El) Yushi Chen*, Changbo Qu, Zhouhan Lin, "SUPERVISED LOCALLY LINEAR EMBEDDING BASED DIMENSI ON REDUCTION FOR HYPERSPECTRAL IMAGE CLASSIFICATION", International Geoscience And Remote Sensing Symposium (IGARSS) 2013, pp: 3578-3581, Melbourne, Australia. (El) Zhouhan Lin, Yushi Chen*, Xing Zhao, Gang Wang, Spectral-Spatial Classification of Hyperspectral Image Using Autoencoders, International Conference on Information, Communications and Signal Processing (ICICS) 2013, pp: 1-5, Taiwan (El) 一种高光谱遥感数据非线性降维方法，中华人民共和国发明专利，专利号201310087912.2 Brief Introduction 名称 Dr. Yushi Chen Department: School of Electronics and Information Engineering Institute: Harbin Institute of Technology Position: Full Professor; PhD Supervisor E-Mail: chenyushi@hit.edu.cn Room: 802, Main building My research interests are in remote sensing data analysis and processing with a special focus on deep learning methods. I proposed the idea of deep learning for hyperspectral images feature extraction and classification. Specifically, I designed a series of deep leaning models including stacked auto-encoder; deep belief network, and 3D convolutional neural network for hyperspectral images classification. I published more than 70 peer-review articles (15 ESI highly-cited papers, including 4 ESI hot papers). I serve as a reviewer for a number of journals including (but not limited to) IEEE TGRS, IEEE JSTARS, and IEEE GRSL.