Aquaculture Areas Extraction Model Using Semantic Segmentation from Remote Sensing Images at the Maowei Sea of Beibu Gulf

Aquaculture Areas Extraction Model Using Semantic Segmentation from Remote Sensing Images at the Maowei Sea of Beibu Gulf

The extraction of aquaculture areas from high-resolution remote sensing images is crucial for effective coastal management and resource preservation. This study introduces SwinNet, a semantic segmentation model leveraging multi-scale feature fusion to enhance the extraction of aquaculture areas, par...

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Bibliographic Details
Main Authors: Weirong Qin, Mohd Hasmadi Ismail, Yangyang Luo, Yifeng Yuan, Junlin Deng, Mohammad Firuz Ramli, Ning Wu
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Fishes
Subjects:
remote sensing images
aquaculture areas
semantic segmentation
swin transformer
multi-scale feature fusion
Online Access:https://www.mdpi.com/2410-3888/10/5/236
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