Extraction of Floating Raft Aquaculture Areas from Sentinel-1 SAR Images by a Dense Residual U-Net Model with Pre-Trained Resnet34 as the Encoder

Extraction of Floating Raft Aquaculture Areas from Sentinel-1 SAR Images by a Dense Residual U-Net Model with Pre-Trained Resnet34 as the Encoder

Marine floating raft aquaculture (FRA) monitoring is significant for marine ecological environment and food security assessment. Synthetic aperture radar-based monitoring is considered to be an effective means of FRA identification because of its capability for all-weather applications. Considering...

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Bibliographic Details
Main Authors: Long Gao, Chengyi Wang, Kai Liu, Shaohui Chen, Guannan Dong, Hongbo Su
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Remote Sensing
Subjects:
floating raft aquaculture
remote sensing
deep learning
residual unit
synthetic aperture radar
Online Access:https://www.mdpi.com/2072-4292/14/13/3003

Internet

https://www.mdpi.com/2072-4292/14/13/3003

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