WE4.R13.1
Sub-Pixel Activity Monitoring in Landsat via Temporal Spectral Complexity
Nicholas Chiaratti, David Messinger, Rochester Institute of Technology, United States
Session:
WE4.R13: Unmixing Analysis Oral
Track:
Theory and Techniques
Location:
Georgetown West
Presentation Time:
Wednesday, 12 August, 16:15 - 16:30
Session Co-Chairs:
Qian Du, Mississippi State University and Nicholas Chiaratti, Rochester Institute of Technology
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Session WE4.R13
WE4.R13.1: Sub-Pixel Activity Monitoring in Landsat via Temporal Spectral Complexity
Nicholas Chiaratti, David Messinger, Rochester Institute of Technology, United States
WE4.R13.2: HYPERSPECTRAL UNMIXING ALGORITHMS WITH EXPLAINABILITY: AN ASSESSMENT OF GEOMETRIC AND DEEP LEARNING METHODS
Utkarsh Anshu Gupta, Air India, India; Soumyashree Kar, Indian Institute of Technology, Bombay, India
WE4.R13.3: A Dual-Attention Hyperspectral Unmixing Network Based on CNN and Swin Transformer
Jiande Zhu, Yufei Liu, School of Communication Engineering, Hangzhou Dianzi University, China; Lei Zhang, School of Computer Science, Northwestern Polytechnical University, China; Na Liu, Xian Zuo, School of Communication Engineering, Hangzhou Dianzi University, China; Zongpeng Li, School of Automation, Hangzhou Dianzi University, China; Shaowei Jiang, School of Communication Engineering, Hangzhou Dianzi University, China
WE4.R13.4: A DEEP EQUILIBRIUM NETWORK FOR HYPERSPECTRAL UNMIXING
Chentong Wang, Jincheng Gao, Fei Zhu, Tianjin University, China; Jie Chen, Northwestern Polytechnical University, China
Resources
No resources available.