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Method for Augmenting Side-Scan Sonar Seafloor Sediment Image Dataset Based on BCEL1-CBAM-INGAN

In this paper, a method for augmenting samples of side-scan sonar seafloor sediment images based on CBAM-BCEL1-INGAN is proposed, aiming to address the difficulties in acquiring and labeling datasets, as well as the insufficient diversity and quantity of data samples. Firstly, a Convolutional Block...

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Principais autores: Haixing Xia, Yang Cui, Shaohua Jin, Gang Bian, Wei Zhang, Chengyang Peng
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2024-09-01
Serier:Journal of Imaging
Fag:
sample amplification
side-scan sonar
background image
convolutional attention mechanism
BCEL1loss function
Online adgang:https://www.mdpi.com/2313-433X/10/9/233
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