基本信息(Overview)教学科研(Teaching & Research)出版物(Publication)English Version
基本信息
陈雨时，工学博士，副教授，博士生导师。

从事人工智能（深度学习）理论及应用、遥感图像分析及处理、医学图像智能诊断的研究。

提出基于深度学习理念的遥感图像处理方法，设计并实现了一系列深度模型用于高光谱遥感图像处理、激光雷达数据处理及多源遥感数据融合，推动了深度学习在遥感领域的应用。

发表学术论文40余篇，SCI收录20余篇（包括ESI高被引论文3篇，ESI热点论文1篇，IEEE GRSS Highest Impact Paper 1篇），SCI引用800余次，Google引用1900余次。

先后主持国家自然科学基金（面上、青年）、国家博士后面上基金、国家重点实验室开放基金、校科研创新基金以及民口横向等多项科研项目；作为核心成员参与国家863某重点项目、总装重点基金、国家自然科学基金等多项科研项目。

文章及代码下载：

https://www.researchgate.net/profile/Yushi_Chen

https://github.com/YushiChen

荣誉奖励
2019年，IEEE GRSS 2019 Highest Impact Paper Award；
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；

2012年，全军武器装备科技进步二等奖；

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
国家自然科学基金 评议人；

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 Enviroment (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（自然科学版）; 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; IEEETransactions 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

工作经历
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


教育经历
1997-092001-07哈尔滨工业大学电子信息工程 工学学士2001-092003-07哈尔滨工业大学信号与信息处理 工学硕士2003-092008-01哈尔滨工业大学信息与通信工程 工学博士


研究生培养
每年招收1名博士生、1-2名硕士生，2-3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。

何 欣（Xin He，2019-D01）

邵广庆（Guangqing Shao，2018-M10）
代广喆（Guangzhe Dai，2018-M09）

朱凯强（Kaiqiang Zhu，2017-M08）

祝琳（Lin Zhu，2017-M07），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

研究领域
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）、深度胶囊网络（Conv-Capsule，2019）等模型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。

讲授课程
主讲以下课程：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）光学与红外遥感卫星定位导航（双语课程）


本科生培养
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（Jiajun Xie，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）


出版物(Publicatoin)
文章及代码下载： https://www.researchgate.net/profile/Yushi_Chen

2019：
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, in press. (SCI, IF: 4.662)

Yushi Chen*, Ying Wang, Yanfeng Gu, Pedram Ghamisi, Xiuping Jia, Deep Learning Ensemble for Hyperspectral Image Classification, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, in press. (SCI, IF: 2.777)
Xin He, Yushi Chen*, Optimized Input for CNN-Based Hyperspectral Image Classification Using Spatial Transformer Network, IEEE Geoscience and Remote Sensing Letters, in press. (SCI, IF: 2.892)

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, 2019, 11(3), 223. (SCI, IF: 3.406)

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 Sensing, in press. (SCI, IF: 4.662)
Xin He, Aili Wang, Pedram Ghamisi, Guoyu Li, Yushi Chen*, LiDAR Data Classification Using Spatial Transformation and CNN, IEEE Geoscience and Remote Sensing Letters, Vol. 16, No. 1, 2019, pp: 125-129. (SCI, IF: 2.892)

Di Wu, Ye Zhang, Yushi Chen, Shengwei Zhong, Vehicle Detection in High-Resolution Images Using Superpixel Segmentation and CNN Iteration Strategy, IEEE Geoscience and Remote Sensing Letters, Vol. 16, No. 1, 2019, pp: 105-109. (SCI, IF: 2.892)
2018：
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)

Aili Wang, Xin He, Pedram Ghamisi, and Yushi Chen*, LiDAR Data Classification Using Morphological Profiles 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, Andrea De Giorgi, Leyuan Fang, Yushi Chen, Mingmin Chi, Sebastiano B. Serpico, Jon Atli Benediktsson, New Frontiers in Spectral-Spatial Hyperspectral Image Classification: The Latest Advances Based on Mathematical 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: 4.932)

2017：
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)

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: 8-32. (SCI, IF: 2.676)

Xi Chen, Gongjian Zhou, Yushi Chen, et al., Supervised Multiview Feature Selection Exploring Homogeneity and Heterogeneity With $ell_{1,2}$ -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 Multiresolution Analysis: A Novel Generalized BDSD Pansharpening Algorithm, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol.10, No.6, 2017, pp: 2867 - 2875. (SCI, IF: 2.913)

2016：

Yushi Chen*, Hanlu Jiang, Chunyang Li, Xiuping Jia, Pedram Ghamisi, Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks, IEEE Transactions on Geoscience and Remote Sensing, Vol. 54, No. 10, 2016, pp: 6232 - 6251. (SCI, IF: 4.942)

Yushi Chen, Chunyang Li, et al., DEEP FUSION OF HYPERSPECTRAL AND LIDAR DATA FOR THEMATIC CLASSIFICATION, International Geoscience And Remote Sensing Symposium (IGARSS) 2016. (EI)

Pedram Ghamisi, Yushi Chen, Xiao Xiang Zhu, A Self-Improving Convolution Neural Network for the Classification 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. (SCI, IF: 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 Fusion 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)

2015：

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)

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 Conference 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, (EI)

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 **2.1

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 **5.7

2014：

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.6, 2014, pp: 2094 - 2107. (SCI, IF: 2.874)

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, Vol.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. (EI)

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. (EI)

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. (EI)

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. (EI)

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 **4.1

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 **5.9

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 **9.8

2013：

Yushi Chen, Zhouhan Lin, Xing Zhao, RIEMANNIAN MANIFOLD LEARNING BASED k-NEAREST-NEIGHBOR FOR HYPERSPECTRAL IMAGE CLASSIFICATION, International Geoscience And Remote Sensing Symposium (IGARSS) 2013, pp: 1975-1978, Melbourne, Australia. (EI)

Yushi Chen, Changbo Qu, Zhouhan Lin, “SUPERVISED LOCALLY LINEAR EMBEDDING BASED DIMENSION REDUCTION FOR HYPERSPECTRAL IMAGE CLASSIFICATION”, International Geoscience And Remote Sensing Symposium (IGARSS) 2013, pp: 3578-3581, Melbourne, Australia. (EI)

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 (EI)

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 **2.2

Dr. Yushi Chen
Department: School of Electronics and Information Engineering

Institute: Harbin Institute of Technology

Position: Associate Professor, PhD Supervisor

E-Mail: chenyushi@hit.edu.cn

Room: 802, Main building

Brief Introduction
Recently, I try to enroll PhD candidates for high impact research.

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 classificaiton. Specifically, I designed a series of deep learing models including stacked auto-encoder, deep belief network, and 3D convolutional neural network for hyperspectral images classification.

I published more than 40 peer-review articles (three ESI highly-cited papers, including one ESI hot paper). I serve as a reviewer for a number of journals including (but not limited to) IEEE TGRS, IEEE JSTARS, and IEEE GRSL.

Seletectd Publications
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, Hanlu Jiang, Chunyang Li, Xiuping Jia, Pedram Ghamisi, Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks, IEEE Transactions on Geoscience and Remote Sensing, Vol. 54, No. 10, 2016, pp: 6232 - 6251. (SCI, IF=4.942, Popular Article) 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, Popular Article) 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.6, 2014, pp: 2094 - 2107. (SCI, IF: 2.874, Popular Article) 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, Vol.7, No.4, 2014, pp: 1295 - 1305. (SCI, IF: 2.874) The detailed information can be found in the following website.

https://www.researchgate.net/profile/Yushi_Chen