Physics-Guided Machine Learning-Based Forward-Modeling of Radar Observables: A Case Study on Sentinel-1 Observations of Corn-Fields
Artificial neural networks have the potential to model the interaction of radar signals with vegetation but often do not follow the physical rules. This article aims to develop a new physics-guided machine learning approach that combines neural networks and physics-based models to leverage their com...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10891699/ |
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