Recent Advances and Trends on Hyperspectral Image Preprocessing, Optimization, and Classification Techniques

Dr. Nian Zhang
Department of Electrical and Computer Engineering, University of the District of Columbia, Washington, D.C., USA

Hyperspectral image classification is an important research topic that focuses on assigning class labels to pixels, which is very challenging because of unbounded size and imbalanced nature of data. This talk will introduce a new computational framework that integrates data preprocessing, optimization, and classification techniques to distinguish trace chemicals from the substrates on which they rest at standoff distances. This talk will first introduce a new data preprocessing method aimed at addressing the class imbalance and unlabeled data challenges commonly encountered in real-world hyperspectral images. Then, a creative approach for extracting endmembers through a global optimization algorithm will be presented. Finally, possible trends and new research directions will be discussed.

Biosketch

Dr. Nian Zhang is a Professor in the Department of Electrical and Computer Engineering at the University of the District of Columbia (UDC), Washington, D.C., USA. She received her Ph.D. degree in Computer Engineering from Missouri University of Science & Technology, USA, and Master’s degree in Automatic Control from Huazhong University of Science and Technology, China. Her research interests include machine learning, deep learning, classification, clustering, and optimization. Dr. Zhang was awarded numerous federal grants from the National Science Foundation, Department of Defense, and National Institutes of Health as the PI/Co-PI, accumulating over $4.5 million in research grant funds. Dr. Zhang serves as an Associate Editor for the IEEE Transactions on Cybernetics, IEEE Transactions on Neural Networks and Learning Systems, Knowledge-Based Systems, and IEEE/CAA Journal of Automatica Sinica. She also serves on the Editorial Board of the Complex & Intelligent Systems. In addition, Dr. Zhang serves as the Chair of the IEEE Computational Intelligence Society (CIS) Task Force on "Interdisciplinary Emergent Technologies" and the Vice Chair of the IEEE CIS’ Adaptive Dynamic Programming and Reinforcement Learning Technical Committee. She regularly serves as the Program Chair and Publications Chair of annual international conferences, including ISNN, ICACI, ICICIP, and ICIST. Dr. Zhang received the IEEE Transactions on Neural Networks and Learning Systems (TNNLS) “Outstanding Associate Editor Award” in 2020. She also received the UDC’s faculty recognition awards for Excellence in Research Award, Excellence in Teaching Award, and Outstanding Undergraduate Research Mentorship Award in three consecutive years.