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湖南大学 副校长 Hunan University
教授 Professor
李树涛,湖南大学教授,博士生导师,湖南大学副校长,兼机器人学院院长,“长江学者”特聘教授,国家“万人计划”领军人才,国家自然科学基金委创新群体负责人。李树涛教授长期围绕图像信息融合、高分辨成像与图像识别开展研究,在国家重点研发计划、国家自然科学基金杰出青年基金等重大重点项目支持下,历经十余年攻关,建立了图像结构化稀疏表示与融合理论体系,提出了高分辨高光谱图像高效识别方法,突破了压缩感知空谱融合成像、多维高分探测、跨模态跨尺度信息融合识别等一系列关键核心技术,研究成果成功应用于航空航天、遥感信息、军事国防等重大战略需求领域,取得了良好的社会和经济效益。相关成果获国家自然科学二等奖1项,国家科技进步二等奖2项,国家科技进步奖创新团队奖1项,省部级科技奖励4项,授权发明专利30余项,在国内外高水平学术期刊和会议发表学术论文300余篇,其中SCI 收录 100 余篇,IEEE 汇刊论文 90余篇,ESI 高被引论文 25 篇,热点论文 5 篇,论文总他引2.7万余次,Web of Science总他引13780余次,连续 5 年入选科睿唯安全球高被引科学家与Elsevier 中国高被引学者。因在图像信息融合与识别上的贡献入选IEEE Fellow。
Professor of Hunan University, doctoral supervisor, vice president of Hunan University, and dean of the School of Robotics, Changjiang Scholar Distinguished Professor of the Ministry of Education, a leading talent of the National "Ten Thousand Talents Program", and the leader of the innovation group of the National Natural Science Foundation of China. Professor Li Shutao has been conducting research on image information fusion, high-resolution imaging and image recognition for a long time. With the support of major key projects such as the National Key R&D Program and the National Natural Science Foundation of China for Distinguished Young Scholars, it has gone through more than ten years of research. He established a theoretical system of image structured sparse representation and fusion, proposed an efficient recognition method for high-resolution and hyper-spectral images, and broke through a series of key cores such as compressed sensing space-spectrum fusion imaging, multi-dimensional high-resolution detection, and cross-modal cross-scale information fusion recognition technology. The research results have been successfully applied to major strategic demand fields such as aerospace, remote sensing information, military defense, etc., and have achieved good social and economic benefits. Relevant achievements have won 1 second prize of the National Natural Science Award, 2 second prizes of the National Science and Technology Progress Award, 1 National Science and Technology Progress Award for Innovation Team, 4 provincial and ministerial science and technology awards, and more than 30 authorized invention patents. He has published more than 300 academic papers in high-level academic journals and conferences at home and abroad, including more than 100 papers included in SCI, more than 90 papers in IEEE Transactions, 25 highly cited papers in ESI, 5 hot papers, and a total of 27,000 papers cited by others. He has been cited more than 13,780 times by Web of Science, and has been selected as Clarivate Global Highly Cited Scientist and Elsevier China Highly Cited Scholar for 5 consecutive years. He was selected as IEEE Fellow for his contribution in image information fusion and recognition.
报告题目:
多模态图像信息智能融合感知
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李树涛,湖南大学教授,博士生导师,湖南大学副校长,兼机器人学院院长,“长江学者”特聘教授,国家“万人计划”领军人才,国家自然科学基金委创新群体负责人。李树涛教授长期围绕图像信息融合、高分辨成像与图像识别开展研究,在国家重点研发计划、国家自然科学基金杰出青年基金等重大重点项目支持下,历经十余年攻关,建立了图像结构化稀疏表示与融合理论体系,提出了高分辨高光谱图像高效识别方法,突破了压缩感知空谱融合成像、多维高分探测、跨模态跨尺度信息融合识别等一系列关键核心技术,研究成果成功应用于航空航天、遥感信息、军事国防等重大战略需求领域,取得了良好的社会和经济效益。相关成果获国家自然科学二等奖1项,国家科技进步二等奖2项,国家科技进步奖创新团队奖1项,省部级科技奖励4项,授权发明专利30余项,在国内外高水平学术期刊和会议发表学术论文300余篇,其中SCI 收录 100 余篇,IEEE 汇刊论文 90余篇,ESI 高被引论文 25 篇,热点论文 5 篇,论文总他引2.7万余次,Web of Science总他引13780余次,连续 5 年入选科睿唯安全球高被引科学家与Elsevier 中国高被引学者。因在图像信息融合与识别上的贡献入选IEEE Fellow。
Professor of Hunan University, doctoral supervisor, vice president of Hunan University, and dean of the School of Robotics, Changjiang Scholar Distinguished Professor of the Ministry of Education, a leading talent of the National "Ten Thousand Talents Program", and the leader of the innovation group of the National Natural Science Foundation of China. Professor Li Shutao has been conducting research on image information fusion, high-resolution imaging and image recognition for a long time. With the support of major key projects such as the National Key R&D Program and the National Natural Science Foundation of China for Distinguished Young Scholars, it has gone through more than ten years of research. He established a theoretical system of image structured sparse representation and fusion, proposed an efficient recognition method for high-resolution and hyper-spectral images, and broke through a series of key cores such as compressed sensing space-spectrum fusion imaging, multi-dimensional high-resolution detection, and cross-modal cross-scale information fusion recognition technology. The research results have been successfully applied to major strategic demand fields such as aerospace, remote sensing information, military defense, etc., and have achieved good social and economic benefits. Relevant achievements have won 1 second prize of the National Natural Science Award, 2 second prizes of the National Science and Technology Progress Award, 1 National Science and Technology Progress Award for Innovation Team, 4 provincial and ministerial science and technology awards, and more than 30 authorized invention patents. He has published more than 300 academic papers in high-level academic journals and conferences at home and abroad, including more than 100 papers included in SCI, more than 90 papers in IEEE Transactions, 25 highly cited papers in ESI, 5 hot papers, and a total of 27,000 papers cited by others. He has been cited more than 13,780 times by Web of Science, and has been selected as Clarivate Global Highly Cited Scientist and Elsevier China Highly Cited Scholar for 5 consecutive years. He was selected as IEEE Fellow for his contribution in image information fusion and recognition.
报告题目:
多模态图像信息智能融合感知