TU4.R9: Physics-Informed Machine Learning in Remote Sensing (2/4)
Oral
Tue, 11 Aug, 16:15 - 17:30
Location: TBD
Session Type: Oral
Session Co-Chairs: Davide De Santis, and Grigorios Tsagkatakis,
Track: Community Contributed Themes
Click the to view the manuscript on IEEE Xplore Open Preview
Tue, 11 Aug, 16:15 - 16:30

TU4.R9.1: Set-Based Transformer for Atmospheric Compensation in Standoff LWIR Hyperspectral Imaging

Fabian Perez, Nicolas Quintero, Jeferson Acevedo, Hoover Rueda-Chacon, Universidad Industrial de Santander, Colombia
Tue, 11 Aug, 16:30 - 16:45

TU4.R9.2: Benchmarking Scientific Machine Learning Models for Air Quality Data

Venkata Sai Rahul Unnam, Khawja Imran Masud, Sahara Ali, University of North Texas, United States
Tue, 11 Aug, 16:45 - 17:00

TU4.R9.3: EXPLAINABLE NEURAL NETWORKS FOR AEROSOL RETRIEVAL: A PRUNING AND SHAP PERSPECTIVE

Davide De Santis, Marco Di Giacomo, Lorenzo Giuliano Papale, Giovanni Schiavon, Fabio Del Frate, "Tor Vergata" University of Rome, Italy
Tue, 11 Aug, 17:00 - 17:15

TU4.R9.4: A Physics-Consistent Reversible Calibration Framework for Multichannel Microwave Data Interpretation: A Case Study in Multi-Soil Parameter Retreival

Yuanhao Cao, Jiayi Du, Shurun Tan, International Campus, Zhejiang University, China
Tue, 11 Aug, 17:15 - 17:30

TU4.R9.5: MULTI-SOURCE UNCERTAINTY AWARE FUSION FOR SOIL MOISTURE ESTIMATION

Eleftherios Polychronakis, Foundation for Research and Technology - Hellas, Greece; Archana Kannan, James Campbell, Mahta Moghaddam, University of Southern California, United States; Panagiotis Tsakalides, Grigorios Tsagkatakis, Foundation for Research and Technology – Hellas, Greece