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个人简介
Wang's research seeks to advance knowledge through modeling objects, concepts, aesthetics, and emotions in big visual data. Formerly with the Biomedical Informatics Group and the Computer Science InfoLab at Stanford, he undertakes work that makes possible the understanding of images based on machine learning and statistical modeling. Among other contributions, he and his collaborators have developed the SIMPLIcity semantics-sensitive image retrieval system, the ALIPR real-time computerized image tagging system, and the ACQUINE aesthetic quality inference engine. Their research has been applied to several domains including biomedical image analysis, satellite imaging, photography, and art and cultural imaging.
Wang's research has been primarily funded by the National Science Foundation. At Penn State, Wang teaches theoretical foundations of information science, discrete mathematics, techniques related to the organization of data, and medical informatics. He also guides a group of both graduate and undergraduate researchers.
Wang's research has been primarily funded by the National Science Foundation. At Penn State, Wang teaches theoretical foundations of information science, discrete mathematics, techniques related to the organization of data, and medical informatics. He also guides a group of both graduate and undergraduate researchers.
研究兴趣
论文共 314 篇作者统计合作学者相似作者
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EXPERT SYSTEMS WITH APPLICATIONSno. Part B (2024): 121520-121520
Zhuomin Zhang, Elizabeth C. Mansfield,Jia Li,John Russell, George S. Young,Catherine Adams, Kevin A. Bowley,James Z. Wang
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCEno. 1 (2024): 33-42
Yimu Pan, Tongan Cai, Manas Mehta,Alison D. Gernand,Jeffery A. Goldstein,Leena Mithal, Delia Mwinyelle,Kelly Gallagher,James Z. Wang
MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION, MICCAI 2023, PT VI (2023): 116-126
Comput. Medical Imaging Graph. (2023): 102236-102236
Internet of Things (2023): 100922-100922
CVPR 2023 (2023): 18993-19004
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