Weakly Supervised Semantic Segmentation of Mangrove Ecosystem Using Sentinel-1 SAR and Deep Convolutional Neural Networks

Mangrove ecosystems are vital blue carbon habitats, and their accurate mapping and ongoing monitoring are essential for conserving their unique ecological and environmental benefits. This study employed a weakly supervised deep learning framework for semantic segmentation of the ecosystem by integra...

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Автори:	Arsalan Ghorbanian, Ardalan Ghorbanian, Seyed Ali Ahmadi, Ali Mohammadzadeh, Amin Naboureh
Формат:	Artigo
Мова:	Inglês
Опубліковано:	IEEE 2025-01-01
Серія:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Предмети:	Deep convolutional neural network (CNN) mangrove semantic segmentation Sentinel-1 synthetic aperture radar (SAR) U-Net
Онлайн доступ:	https://ieeexplore.ieee.org/document/11072052/
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Weakly Supervised Semantic Segmentation of Mangrove Ecosystem Using Sentinel-1 SAR and Deep Convolutional Neural Networks

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