Generating Synthetic Sidescan Sonar Snippets Using Transfer-Learning in Generative Adversarial Networks

Generating Synthetic Sidescan Sonar Snippets Using Transfer-Learning in Generative Adversarial Networks

The training of a deep learning model requires a large amount of data. In case of sidescan sonar images, the number of snippets from objects of interest is limited. Generative adversarial networks (GAN) have shown to be able to generate photo-realistic images. Hence, we use a GAN to augment a baseli...

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Bibliographic Details
Main Authors: Yannik Steiniger, Dieter Kraus, Tobias Meisen
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Journal of Marine Science and Engineering
Subjects:
deep learning
generative adversarial networks
transfer-learning
sidescan sonar
synthetic sonar images
Online Access:https://www.mdpi.com/2077-1312/9/3/239

Internet

https://www.mdpi.com/2077-1312/9/3/239

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