Water-Body Type Classification in Dual PolSAR Imagery Using a Two-Step Deep-Learning Method

Water-Body Type Classification in Dual PolSAR Imagery Using a Two-Step Deep-Learning Method

Water-body type problems classification plays a vital role in ecological conservation, water resource management, and urban planning. Accurate classification can aid decision-makers in understanding the functions of different water-body types, providing key information for urban planning and promoti...

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Bibliographic Details
Main Authors: Qiming Yuan, Jing Lu, Lin Wu, Yabo Huang, Zhengwei Guo, Ning Li
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Deep learning
feature fusion
hyperparameter optimize
polarization decomposition method
synthetic aperture radar (SAR)
water-body types classification
Online Access:https://ieeexplore.ieee.org/document/10418484/

Internet

https://ieeexplore.ieee.org/document/10418484/

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