西安电子科技大学人工智能学院导师教师师资介绍简介-焦李成

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基本信息
焦李成　教授博士生导师
智能感知与图像理解教育部重点实验室主任
工作单位：人工智能学院

主要研究方向
模式识别与人工智能
图像智能感知与自然计算
类脑计算与大数据

联系方式
通信地址：西安电子科技大学224信箱邮编710071
电子邮箱：lchjiao@mail.xidian.edu.cn
办公电话：
办公地点：主楼2区401

相关链接
西安电子科技大学
人工智能学院
智能感知与图像理解重点实验室

焦李成教授博导
华山****领军教授、博士生导师
计算机科学与技术学部主任
人工智能研究院院长
俄罗斯自然科学院外籍院士
欧洲科学院外籍院士
智能感知与图像理解教育部重点实验室主任
智能感知与计算国际联合研究中心主任
智能感知与计算国际合作联合实验室主任
教育部“****支持计划”创新团队首席
国家“111”计划智能信息处理创新引智基地主任
陕西省大数据智能感知与计算2011协同创新中心主任
中国人工智能学会会士
中国计算机学会会士
中国电子学会会士
中国自动化学会会士
IEEE/IETFellow
教育部科技委学部委员
教育部人工智能科技创新专家组专家
“一带一路”人工智能创新联盟理事长
陕西省人工智能产业技术创新战略联盟理事长
西安市人工智能产业发展联盟理事长
IEEE计算智能学会西安chapter主席
IEEE地理遥感学会西安chapter主席
IEEE西安分会奖励委员会主席
IET西安分会主席

个人简介
焦李成，男，1959年10月出生于陕西白水。分别于1982年、1984年和1990年在上海交通大学、西安交通大学获学士、硕士、博士学位，1990年5月至1992年5月，在西安电子科技大学雷达信号处理国家重点实验室从事博士后研究，任讲师、副教授。1992年6月至2003年3月，任西安电子科技大学雷达信号处理国家重点实验室教授，博士生导师。现任西安电子科技大学计算机科学与技术学部主任、人工智能研究院院长、智能感知与图像理解教育部重点实验室主任、智能感知与计算国际联合研究中心主任、智能感知与计算国际合作联合实验室主任、“智能信息处理科学与技术”高等学校学科创新引智基地（“111计划”）主任、教育部科技委学部委员、中国人工智能学会副理事长、教育部人工智能科技创新专家组专家、IET西安分会主席、IEEE西安分会奖励委员会主席、IEEE计算智能协会西安分会主席、IEEE GRSS西安分会主席，IEEE TCYB、IEEE TGRS副主编、教育部创新团队首席专家，IEEE Fellow、IET Fellow、CAAI Fellow、CCF Fellow、CIE Fellow、CAA Fellow，PC of NeurlPS、ICML、CVPR、AAAI、IJCAI and ICCV,连续七年入选爱思唯尔高被引****榜单。国务院学位委员会学科评议组成员，人社部博士后管委会评议组专家，曾任第八届全国人大代表。1991年被批准为享受国务院政府津贴的专家，1996年首批入选国家“百千万”人才工程（第一、二层次），陕西省首批“三五人才”第一层次。当选为全国模范教师、陕西省突出贡献专家和陕西省师德标兵。
新版个人主页：https://faculty.xidian.edu.cn/JLC/zh_CN/index.htm
谷歌学术主页：https://scholar.google.com/citations?user=FZbrL2YAAAAJ&hl=en
DBLP学术主页：https://dblp.org/pid/40/3714.html

科学研究

三十年多来，焦李成教授一直针对海量、高维、非结构化信息处理中的优化与学习问题展开科研工作，对基于计算智能的学习与优化理论及其在复杂影像解译中的应用进行了深入研究，并取得了一系列科研成果。与此同时，也培养出了多名人工智能领域的杰出人才。
海量、高维、非结构化信息处理中的优化与学习问题一直是国际学术界公认的难题，焦李成教授带领团队在这一领域耕耘数十年，取得了一批原创性的学术成果，提出了免疫进化优化理论框架与协同进化优化框架，并于2013年荣获国家自然科学奖二等奖。面向复杂影像内容解译中的诸多瓶颈问题，焦李成教授提出了高维奇异性多尺度检测的概念与理论，包括小波SVM、稀疏快速SVM、脊波神经网络及曲线波网络等，建立了用于复杂影像的预处理、图像分析和数据压缩的方法和技术，研发了深度学习FPGA系统、遥感影像大数据类脑解译系统、国内首个类脑SAR系统等，打破了国外对我国的技术封锁与禁运，相关成果荣获四项教育部自然科学一等奖、陕西省科学技术一等奖。
焦李成教授的学术成果得到了国际同行的认可与广泛引用，Google Scholar H指数为84，由于其在科学与工程技术领域、人工智能领域人工神经网络及进化计算方向的杰出贡献当选为IEEE Fellow、IET Fellow、CAAI Fellow、CCF Fellow、CIE Fellow、CAA Fellow，IEEE TCYB、IEEE TGRS等领域主流期刊副主编。PC of NeurlPS、ICML、CVPR、AAAI、IJCAI and ICCV.。焦李成教授曾先后荣获霍英东青年教师奖、全国模范教师称号、中国青年科技奖，首批入选国家百千****才工程（第一二层次），是教育部****计划创新团队负责人，培养了多名博士、博士后、973首席科学家、****、“****”领军人才等****专家，京东金融首席科学家，商汤科技CTO，阿里达摩院战略专家等产业界翘楚；出版了《神经网络系统理论》、《免疫优化计算、学习与识别》、《深度学习、优化与识别》、《人工智能、类脑计算与图像解译前沿》、《遥感影像智能解译与识别》、《雷达图像解译技术》等领域内我国的首部专著，启蒙了一代AI领域的研究者。焦李成教授的学术及教学成果为我国人工智能领域的科学研究与人才培养起到了积极的促进和指导作用。

学术论文
代表专著：
序号作者书名出版社出版年份1 焦李成神经网络系统理论西安电子科技大学出版社 1990
2 焦李成非线性传递函数理论与应用西安电子科技大学出版社 1992
3 焦李成神经网络计算西安电子科技大学出版社 1993
4 焦李成神经网络的应用与实现西安电子科技大学出版社 1996
5 焦李成免疫优化计算、学习与识别科学出版社 2006
6 焦李成、刘芳、缑水平智能数据挖掘与知识发现西安电子科技大学出版社 2006
7 Jiao Licheng, Jing Liu and Weicai Zhong Coevolutionary Computation and Multiagent Systems WIT Press, UK/科学出版社 2012
8 焦李成、冯婕、刘芳、杨淑媛、张向荣高分辨遥感影像学习与感知科学出版社 2017
9 焦李成、李阳阳、刘芳、马文萍、尚荣华量子计算、优化与学习科学出版社 2017
10 焦李成、赵进、杨淑媛、刘芳深度学习、优化与识别清华大学出版社 2017
11 焦李成、侯彪、尚荣华、杨淑媛、王爽、万红林、辛芳芳、刘赶超智能SAR影像变化检测科学出版社 2017
12 焦李成、侯彪、王爽、刘芳、杨淑媛、白静、钟桦雷达图像解译技术国防工业出版社 2017
13 焦李成、尚荣华、刘芳、杨淑媛、侯彪、王爽、马文萍认知计算与多目标优化科学出版社 2017
14 焦李成、尚荣华、刘芳、杨淑媛、侯彪、王爽、马文萍稀疏学习、分类与识别科学出版社 2017
15 焦李成、刘芳、李玲玲、杨淑媛、侯彪、杨争艳、杨慧、孟繁荣遥感影像深度学习智能解译与识别西安电子科技大学出版社 2019
16 焦李成、刘若辰、慕彩红、刘芳简明人工智能西安电子科技大学出版社 2019
17 焦李成，侯彪，唐旭，刘芳，杨淑媛，陈莉，马文萍等人工智能、类脑计算与图像解译前沿西安电子科技大学出版社 2019
18 焦李成、李阳阳、侯彪、石光明、张丹、田小林、李欣越、缑水平、王爽、张向荣、杨韦洁人工智能学院本硕博培养体系清华大学出版社 2019
19 Jiao, Licheng, Ronghua Shang, Fang Liu, and Weitong Zhang. Brain and Nature-Inspired Learning, Computation and Recognition. Elsevier, 2020.
20 焦李成、孙其功、邬刚、田小林、陈永、侯彪、杨淑媛深度神经网络FPGA设计与实现西安电子科技大学出版社 2021
代表论文：
[1] Jiao L, Zhang R, Liu F, et al. New Generation Deep Learning for Video Object Detection: A Survey[J]. IEEE Transactions on Neural Networks and Learning Systems, 2021.
[2] Li A, Jiao L, Zhu H, et al. Multitask Semantic Boundary Awareness Network for Remote Sensing Image Segmentation[J]. IEEE Transactions on Geoscience and Remote Sensing, 2021.
[3] Liu X, Jiao L, Li L, et al. Deep Multiview Union Learning Network for Multisource Image Classification[J]. IEEE Transactions on Cybernetics, 2020.
[4] Wang H, Jiao L, Yang S, et al. Simple and Effective: Spatial Rescaling for Person Reidentification[J]. IEEE Transactions on Neural Networks and Learning Systems, 2020.
[5] Liu M, Jiao L, Liu X, et al. C-CNN: Contourlet Convolutional Neural Networks[J]. IEEE Transactions on Neural Networks and Learning Systems, 2020.
[6] Zhu, Hao, Wenping Ma, Lingling Li, Licheng Jiao, Shuyuan Yang, and Biao Hou. "A DualCBranch Attention fusion deep network for multiresolution remoteCSensing image classification." Information Fusion 58 (2020): 116-131.
[7] Wang, Shigang, Shuyuan Yang, Min Wang, and Licheng Jiao. "New Contour Cue- Based Hybrid Sparse Learning for Salient Object Detection." IEEE Transactions on Cybernetics (2019).
[8] Mao, Shasha, Weisi Lin, Licheng Jiao, Shuiping Gou, and Jia-Wei Chen. "End-to- End Ensemble Learning by Exploiting the Correlation Between Individuals and Weights." IEEE Transactions on Cybernetics (2019).
[9] Feng, Zhixi, Shuyuan Yang, Min Wang, and Licheng Jiao. "Learning Dual Geomet- ric Low-Rank Structure for Semisupervised Hyperspectral Image Classification." IEEE Transactions on Cybernetics (2019).
[10] Zhu, Hao, Licheng Jiao, Wenping Ma, Fang Liu, and Wei Zhao. “A Novel Neural Net- work for Remote Sensing Image Matching." IEEE Transactions on Neural Networks and Learning Systems (2019).
[11] Liu, Fang, Licheng Jiao, and Xu Tang. “Task-Oriented GAN for PolSAR Image Clas- sification and Clustering." IEEE Transactions on Neural Networks and Learning Systems (2019).
[12] Liu, Bo, Wenlian Lu, Licheng Jiao, and Tianping Chen. "Products of Generalized Stochastic Matrices With Applications to Consensus Analysis in Networks of Multiagents With Delays." IEEE Transactions on Cybernetics 50, no. (2018): 386-399.
[13] Luo, Juanjuan, Licheng Jiao, Fang Liu, Shuyuan Yang, and Wenping Ma. "A Pareto- Based Sparse Subspace Learning Framework." IEEE Transactions on Cybernetics 49, no. 1(2018): 3859-3872.
[14] Guo, Yuwei, Licheng Jiao, Shuang Wang, Shuo Wang, and Fang Liu. "Fuzzy sparse autoencoder framework for single image per person face recognition." IEEE transactions on cybernetics 48, no. 8 (2017): 2402-2415.
[15] Liu, Fang, Licheng Jiao, Xu Tang, Shuyuan Yang, Wenping Ma, and Biao Hou. “Local Restricted Convolutional Neural Network for Change Detection in Polarimetric SAR Im- ages." IEEE Transactions on Neural Networks and Learning Systems 99 (2018): 1-16.
[16] Guo, Yuwei, Licheng Jiao, Shuang Wang, Shuo Wang, Fang Liu, and Wenqiang Hua. “Fuzzy superpixels for polarimetric SAR images classification." IEEE Transactions on Fuzzy Systems 26, no. 5 (2018): 2846-2860.
[17] Gu, Jing, Licheng Jiao, Shuyuan Yang, and Fang Liu. “Fuzzy double C-means clustering based on sparse self-representation." IEEE Transactions on Fuzzy Systems 26, no. 2 (2017): 612-626.
[18] Liu, Xu, Licheng Jiao, Xu Tang, Qigong Sun, and Dan Zhang. “Polarimetric Convolu- tional Network for PolSAR Image Classification." IEEE Transactions on Geoscience and Remote Sensing (2018).
[19] Chen, Yanqiao, Licheng Jiao, Yangyang Li, Lingling Li, Dan Zhang, Bo Ren, and Naresh Marturi. “A Novel Semicoupled Projective Dictionary Pair Learning Method for PolSAR Image Classification." IEEE Transactions on Geoscience and Remote Sensing (2018).
[20] Wen, Zaidao, Biao Hou, Qian Wu, and Licheng Jiao. "Discriminative transformation learning for fuzzy sparse subspace clustering." IEEE Transactions on Cybernetics 48, no. 8 (2017): 2218-2231.
Google Scholar地址：
https://scholar.google.com/citations?user=FZbrL2YAAAAJ&hl=en

荣誉获奖
焦李成教授的学术成果得到了国际同行的认可与广泛引用，Google Scholar H指数为84，由于其在科学与工程技术领域、人工智能领域人工神经网络及进化计算方向的杰出贡献当选为IEEE Fellow、IET Fellow、CAAI Fellow、CCF Fellow、CIE Fellow、CAA Fellow，IEEE TCYB、IEEE TGRS等领域主流期刊副主编。PC of NeurlPS、ICML、CVPR、AAAI、IJCAI and ICCV.。焦李成教授曾先后荣获霍英东青年教师奖、全国模范教师称号、中国青年科技奖，首批入选国家百千****才工程（第一二层次），吴文俊人工智能杰出贡献奖。焦李成教授是教育部****计划创新团队负责人，培养了多名博士、博士后、973首席科学家、****、“****”领军人才等****专家，京东金融首席科学家，商汤科技CTO，阿里达摩院战略专家等产业界翘楚；出版了《神经网络系统理论》、《免疫优化计算、学习与识别》、《深度学习、优化与识别》、《人工智能、类脑计算与图像解译前沿》、《遥感影像智能解译与识别》、《雷达图像解译技术》等领域内我国的首部专著，启蒙了一代AI领域的研究者。焦李成教授的学术及教学成果为我国人工智能领域的科学研究与人才培养起到了积极的促进和指导作用。

科研团队
西安电子科技大学计算机科学与技术学部主任、教授、博士生导师
智能感知与图像理解教育部重点实验室主任
智能感知与计算国际联合研究中心主任
智能感知与计算国际合作联合实验室主任
教育部“****支持计划”创新团队首席
国家“111”计划智能信息处理创新引智基地主任
陕西省大数据智能感知与计算2011协同创新中心主任

Profile

Licheng Jiao
Distinguished/Chair Professor

Research Interests
Artificial Intelligence
Pattern Recognition
Image Intelligent Perception
Natural Computation
Brainlike Learning
Big Data

Introduction
Licheng Jiao has been a professor in Xidian University since 1992. Now, he is the distinguished/chair/director professor of the Faculty of Computer Science and Technology of Xidian University, Dean of AI research institute, International Research Center for Intelligent Perception and Computation, Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Joint International Research Laboratory of Intelligent Perception and Computation, and National 111 Project Base of Intelligent Information Processing. His professional activities include IEEE/IET/CAAI/CAA/CIE/CCF Fellow, the member of the International Division of Scientific and Technological Committee of the Ministry of Education in China, the vice board chairperson of Chinese Association of Artificial Intelligence. He is the chairman of IET Xi’an Network, the Xi’an Chapter of IEEE Computational Intelligence Society, the Award Commission of IEEE Xi’an Chapter, and the Xi’an Chapter of IEEE Geoscience and Remote Sensing Society. He is the Associate Editor of “IEEE Transactions on Geoscience and Remote Sensing”, the Presiding Panelist for the Innovative Team in the Ministry of Education, the member of the Subject Consultative Group of the State Council and the expert of the Undergraduate Teaching Level Evaluation of the Ministry of Education, evaluation expert of the National Natural Science Foundation Information Division, member of the Assessment Panel of National Postdoctoral Management Committees.
He has been receiving special government allowance from the State Council since 1991. In 1996, he was included among the first batch of in the New Century Talents Project (the first and second classes) and the “Three Fives” Talent Project of Shaanxi Province. He was selected as the National Model Teacher by the Ministry of Human Resources and Social Security of China, the Outstanding Contribution Expert of Shaanxi Province, the Teacher Pacemaker of Ethics in Shaanxi Province, and the deputy of the 8th National People’s Congress.

The research direction of Prof. Jiao includes intelligent perception and image understanding, image understanding and object recognition, deep learning and brain-inspired computation. More than 10 of his students have won the National Excellent Doctoral Dissertation Award and nomination, or the Shaanxi Province Excellent Doctoral Dissertation Award. His research results have won the Youth Science and Technology Award, the Second Prize of National Natural Science Award and several provincial-level first Prizes. More than 10 Academic monographs have been published.

Contact Information
Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China,
P. O. Box 224, Xidian University, Xi\\\\\\\\'an, 710071, China
Phone: +86 29 8820 1023 (Prof. Licheng Jiao)
Fax: +86 29 8820 1023
Email: lchjiao@mail.xidian.edu.cn

Profile

Contact Information
Address:North Campus: No. 2 South Taibai Road, Xi’an, Shaanxi 710071
Email: lchjiao@mail.xidian.edu.cn
Tel:

Introduction
Licheng Jiao received the B.S.degree from Shanghai Jiaotong University, Shanghai, China, in 1982 and the M.S. and PhD degree from Xi’an Jiaotong University, Xi’an, China, in 1984 and 1990, respectively. Since 1992, he has been a ChairProfessor with the school of Artificial Intelligence, Xidian University, Xi’an, where he is currently the Director of Key Laboratory of Intelligent Perception and Image Understanding of the Ministry of Education of China. His research interests include image processing, natural computation, machine learning, and intelligent information processing. Dr. Jiao is the Chairman of the Awards and Recognition Committee, the Vice Board Chairperson of the Chinese Association of Artificial Intelligence, the fellow of IEEE/IET/CAAI/CIE/CCF/CAA, PC of NeurlPS、ICML、CVPR、AAAI、IJCAI and ICCV. ACouncilor of the Chinese Institute of Electronics, a committee member of the Chinese Committee of Neural Networks, and an expert of the Academic Degrees Committee of theState Council.
Google Scholar: https://scholar.google.com/citations?user=FZbrL2YAAAAJ&hl=en

Research Interests
1．Intelligent perception and Computing
2．Image understanding and target recognition
3．Deep learning and brain-inspired computing

Research
目前研究团队承担的科研项目：

Papers
Google Scholar: https://scholar.google.com/citations?user=FZbrL2YAAAAJ&hl=en
[1] Zhu, Hao, Wenping Ma, Lingling Li, Licheng Jiao, Shuyuan Yang, and Biao Hou. "A DualCBranch Attention fusion deep network for multiresolution remote Sensing image classification." Information Fusion 58 (2020): 116-131.
[2] Wang, Shigang, Shuyuan Yang, Min Wang, and Licheng Jiao. "New Contour Cue- Based Hybrid Sparse Learning for Salient Object Detection." IEEE Transactions on Cybernetics (2019).
[3] Mao, Shasha, Weisi Lin, Licheng Jiao, Shuiping Gou, and Jia-Wei Chen. "End-to-End Ensemble Learning by Exploiting the Correlation Between Individuals and Weights." IEEE Transactions on Cybernetics (2019).
[4] Feng, Zhixi, Shuyuan Yang, Min Wang, and Licheng Jiao. "Learning Dual Geomet- ric Low-Rank Structure for Semisupervised Hyperspectral Image Classification." IEEE Transactions on Cybernetics (2019).
[5] Zhu, Hao, Licheng Jiao, Wenping Ma, Fang Liu, and Wei Zhao. “A Novel Neural Net- work for Remote Sensing Image Matching." IEEE Transactions on Neural Networks and Learning Systems (2019).
[6] Liu, Fang, Licheng Jiao, and Xu Tang. “Task-Oriented GAN for PolSAR Image Clas- sification and Clustering." IEEE Transactions on Neural Networks and Learning Systems (2019).
[7] Liu, Bo, Wenlian Lu, Licheng Jiao, and Tianping Chen. "Products of Generalized Stochastic Matrices With Applications to Consensus Analysis in Networks of Multiagents With Delays." IEEE Transactions on Cybernetics 50, no. 1 (2018): 386-399.
[8] Luo, Juanjuan, Licheng Jiao, Fang Liu, Shuyuan Yang, and Wenping Ma. "A Pareto- Based Sparse Subspace Learning Framework." IEEE Transactions on Cybernetics 49, no. 11 (2018): 3859-3872.
[9] Guo, Yuwei, Licheng Jiao, Shuang Wang, Shuo Wang, and Fang Liu. "Fuzzy sparse autoencoder framework for single image per person face recognition." IEEE transactions on cybernetics 48, no. 8 (2017): 2402-2415.
[10] Liu, Fang, Licheng Jiao, Xu Tang, Shuyuan Yang, Wenping Ma, and Biao Hou. “Local Restricted Convolutional Neural Network for Change Detection in Polarimetric SAR Im- ages." IEEE Transactions on Neural Networks and Learning Systems 99 (2018): 1-16.
[11] Guo, Yuwei, Licheng Jiao, Shuang Wang, Shuo Wang, Fang Liu, and Wenqiang Hua. “Fuzzy superpixels for polarimetric SAR images classification." IEEE Transactions on Fuzzy Systems 26, no. 5 (2018): 2846-2860.
[12] Gu, Jing, Licheng Jiao, Shuyuan Yang, and Fang Liu. “Fuzzy double C-means clustering based on sparse self-representation." IEEE Transactions on Fuzzy Systems 26, no. 2 (2017): 612-626.
[13] Liu, Xu, Licheng Jiao, Xu Tang, Qigong Sun, and Dan Zhang. “Polarimetric Convolu-tional Network for PolSAR Image Classification." IEEE Transactions on Geoscience and Remote Sensing (2018).
[14] Chen, Yanqiao, Licheng Jiao, Yangyang Li, Lingling Li, Dan Zhang, Bo Ren, and Naresh Marturi. “A Novel Semicoupled Projective Dictionary Pair Learning Method for PolSAR Image Classification." IEEE Transactions on Geoscience and Remote Sensing (2018).
[15] Wen, Zaidao, Biao Hou, Qian Wu, and Licheng Jiao. "Discriminative transformation learning for fuzzy sparse subspace clustering." IEEE Transactions on Cybernetics 48, no. 8 (2017): 2218-2231.
[16] Zhang, Sibo, Licheng Jiao, Fang Liu, and ShuangWang. "Global low-rank image restora- tion with Gaussian mixture model." IEEE Transactions on Cybernetics 48, no. 6 (2017): 1827-1838.
[17] Lin, Leping, Fang Liu, Licheng Jiao, Shuyuan Yang, and Hongxia Hao. "The overcom- plete dictionary-based directional estimation model and nonconvex reconstruction meth- ods." IEEE Transactions on Cybernetics 48, no. 3 (2017): 1042-1053.
[18] Shang, Ronghua, Wenbing Wang, Rustam Stolkin, and Licheng Jiao. "Non-negative spectral learning and sparse regression-based dual-graph regularized feature selection." IEEE Transactions on Cybernetics 48, no. 2 (2017): 793-806.
[19] Chen, Yanqiao, Licheng Jiao, Yangyang Li, and Jin Zhao. “Multilayer projective dic- tionary pair learning and sparse autoencoder for PolSAR image classification." IEEE Transactions on Geoscience and Remote Sensing 55, no. 12 (2017): 6683-6694.
[20] Tang, Xu, Licheng Jiao, William J. Emery, Fang Liu, and Dan Zhang. “Two-stage reranking for remote sensing image retrieval." IEEE Transactions on Geoscience and Remote Sensing 55, no. 10 (2017): 5798-5817.
[21] Jiao, Licheng, Miaomiao Liang, Huan Chen, Shuyuan Yang, Hongying Liu, and Xi- anghai Cao. “Deep fully convolutional network-based spatial distribution prediction for hyperspectral image classification." IEEE Transactions on Geoscience and Remote Sensing 55, no. 10 (2017): 5585-5599.
[22] Liu, Xu, Licheng Jiao, Jiaqi Zhao, Jin Zhao, Dan Zhang, Fang Liu, Shuyuan Yang, and Xu Tang. “Deep multiple instance learning-based spatialCspectral classification for PAN and MS imagery." IEEE Transactions on Geoscience and Remote Sensing 56, no. 1 (2017): 461-473.
[23] Zhao, Wei, Licheng Jiao, Wenping Ma, Jiaqi Zhao, Jin Zhao, Hongying Liu, Xianghai Cao, and Shuyuan Yang. “Superpixel-based multiple local CNN for panchromatic and multispectral image classification." IEEE Transactions on Geoscience and Remote Sensing 55, no. 7 (2017): 4141-4156.
[24] Tang, Xu, Licheng Jiao, and William J. Emery. “SAR image content retrieval based on fuzzy similarity and relevance feedback." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10, no. 5 (2017): 1824-1842.
[25] Xie, Wen, Licheng Jiao, Biao Hou, Wenping Ma, Jin Zhao, Shuyin Zhang, and Fang Liu. “POLSAR image classification via Wishart-AE model or Wishart-CAE model." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10, no. 8 (2017): 3604-3615.
[26] Chen, Yanqiao, Yangyang Li, Licheng Jiao, Cheng Peng, Xiangrong Zhang, and Ronghua Shang. “Adversarial Reconstruction-Classification Networks

Honors
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Team
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Teaching
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Admission
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