Revealing the Potential of Deep Learning for Detecting Submarine Pipelines in Side-Scan Sonar Images: An Investigation of Pre-Training Datasets

Revealing the Potential of Deep Learning for Detecting Submarine Pipelines in Side-Scan Sonar Images: An Investigation of Pre-Training Datasets

This study introduces a novel approach to the critical task of submarine pipeline or cable (POC) detection by employing GoogleNet for the automatic recognition of side-scan sonar (SSS) images. The traditional interpretation methods, heavily reliant on human interpretation, are replaced with a more r...

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Bibliographic Details
Main Authors: Xing Du, Yongfu Sun, Yupeng Song, Lifeng Dong, Xiaolong Zhao
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Remote Sensing
Subjects:
side-scan sonar
convolutional neural networks
transfer learning
geological survey
GoogleNet
Yellow River Estuary
Online Access:https://www.mdpi.com/2072-4292/15/19/4873

Internet

https://www.mdpi.com/2072-4292/15/19/4873

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