Prof. Hong Huang, Chongqing University
Title: Remote Sensing Image Scene Classification from High Spatial Resolution to hyperspectral Resolution
Abstract: For Remote sensing scene classification, extracting scene-level discriminative features is key to bridging the gap between low-level visual attributes and high-level semantic information of images. Based on deep learning, graph learning and vision transformer, some end-to-end frameworks have proposed for scene classification, and the proposed methods achieved good accuracies by mining high-level semantic information and context features of remote sensing images. However, high spatial resolution (HSR) images contain extremely limited spectral information, and they are prone to misclassification of scenes with similar visual perception, while hyperspectral images (HSIs) possess rich spectral information, which can be used for material identification. Existing HSI datasets are mainly oriented to pixel-wise classification, which are difficult to be directly applied to scene-level image interpretation. In view of this, a hyperspectral remote sensing dataset is constructed for scene classification (HSRS-SC). To evaluate classification performance, several deep learning models are employed under different training samples, and results show that the HSRS-SC can reflect detailed spatial-spectral information.
Experience: Huang Hong is a Professor and Ph. D Supervisor in the College of Optoelectric Engineering, Chongqing University, China. He also is a head of Department of Measurement and Control Technology and Instruments, and the director of the Image Information Processing Laboratory, Chongqing University, China. His main research activities are in the fields of image processing, pattern recognition, and remote sensing. In particular, he pays more attention to manifold learning, deep learning, graph learning, and hyperspectral remote sensing. Dr. Huang has published more than 100 journal articles and conference papers, and obtained ten invention patent authorizations. He is a guest Associate Editor of Frontier in Oncology and a guest Editor of Applied Sciences, and a Reviewer of over 20 international journals, including IEEE Trans. Geoscience and Remote Sensing, IEEE Trans. Cybernetics, IEEE Trans. Neural Networks and Learning Systems, and IEEE Transactions on Medical Imaging. Dr. Huang has won the second prize of China Machinery Industry Science and Technology Progress Award.
A. Prof. Qingzhi Zhao, Xi'an University of Science and Technology
Title: Coming Soon
Abstract: Coming Soon
Experience: Mainly engaged in the teaching of "Satellite Navigation and Positioning Principles and Applications", "Engineering Surveying" and other courses. The research direction is GNSS data processing, GNSS and satellite remote sensing and other multi-source water vapor inversion and application research. In the past five years, more than 50 SCI/EI academic papers have been published in related fields, including more than 30 SCI papers by the first author and corresponding author; 2 authorized invention patents and 3 software copyrights; Excellent scientific research in colleges and universities Achievement Award (Science and Technology) Science and Technology Progress Award, the first prize and many other provincial and ministerial awards; undertaking a number of scientific research projects such as the National Natural Science Foundation of China, the Shaanxi Provincial Natural Science Basic Research Project, and the Shaanxi Provincial Department of Education Scientific Research Project. Won the title of "The 4th Science and Technology Rising Star of Xi'an University of Science and Technology" and "The 6th Xu Jinghua Young Teacher Award of Xi'an University of Science and Technology".
2022 International Conference on Remote Sensing, Surveying and Mapping (RSSM 2022) http://icrssm.net/