WE3.P11.3
Foundation Model for Multi-sources Hyperspectral Images Interpretation
Baisen Liu, Xinyao Li, Heilongjiang Institute of Technology, China; Wen Zhang, Shanghai Surveying and Mapping Institute, China; Weili Kong, Harbin Engineering University, China
Session:
WE3.P11: AI Impact and On-board Hyperspectral Data Analytics I Oral
Track:
Community-Contributed Sessions
Location:
Room P11
Presentation Time:
Wednesday, 6 August, 13:45 - 14:00
Presentation
Discussion
Resources
No resources available.
Session WE3.P11
WE3.P11.1: AN EFFICIENT MULTI-DIRECTION STATE SPACE MODEL FOR HYPERSPECTRAL RECONSTRUCTION
Chengle Zhou, Zhi He, Li Wang, Sun Yat-Sen University, China
WE3.P11.2: Low-Rank and Sparse Prior-Informed Class-Subspace Learning Network for Hyperspectral Image Classification
Xiangyu Nie, Zhaohui Xue, Hohai University, China
WE3.P11.3: Foundation Model for Multi-sources Hyperspectral Images Interpretation
Baisen Liu, Xinyao Li, Heilongjiang Institute of Technology, China; Wen Zhang, Shanghai Surveying and Mapping Institute, China; Weili Kong, Harbin Engineering University, China
WE3.P11.4: SAMPLE SIMILARITY-GUIDED SPATIAL-SPECTRAL MASKED AUTOENCODER FOR HYPERSPECTRAL ANOMALY DETECTION
Zhe Zhao, Jiajia Zhang, Jiangluqi Song, Pei Xiang, Xidian University, China; Dong Zhao, Wuxi University, China; Huixin Zhou, Xidian University, China
WE3.P11.5: GRAPH COLLABORATIVE REPRESENTATION WITH LOW-RANK DISCRIMINATIVE DICTIONARY FOR HYPERSPECTRAL ANOMALY DETECTION
Yufan Yang, Weimeng Xu, Hui Shen, Hengyi Zheng, Hongjun Su, Hohai University, China; Qian Du, Mississippi State University, United States
Resources
No resources available.