Target Detection and Segmentation in Circular-Scan Synthetic Aperture Sonar Images Using Semisupervised Convolutional Encoder

Target Detection and Segmentation in Circular-Scan Synthetic Aperture Sonar Images Using Semisupervised Convolutional Encoder–Decoders

Published:2022-10 Issue:4 Volume:47 Page:1099-1128
ISSN:0364-9059
Container-title:IEEE Journal of Oceanic Engineering
language:
Short-container-title:IEEE J. Oceanic Eng.

Author:

Sledge Isaac J.¹^ORCID,Emigh Matthew S.¹,King Jonathan L.²,Woods Denton L.³^ORCID,Cobb J. Tory¹,Principe Jose C.⁴

Affiliation:

1. Advanced Signal Processing and Automated Target Recognition Branch, Naval Surface Warfare Center, Panama City, FL, USA

2. Applied Sensing and Processing Branch, Naval Surface Warfare Center, Panama City, FL, USA

3. Littoral Acoustics and Target Physics Branch, Naval Surface Warfare Center, Panama City, FL, USA

4. Department of Electrical and Computer Engineering, with the Department of Biomedical Engineering, and with the Computational Neuroengineering Laboratory, University of Florida, Gainesville, FL, USA

Funder

Office of Naval Research

In-House Laboratory Independent Research

Naval Sea Systems Command

Naval Innovation in Science and Engineering

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Ocean Engineering

Link

http://xplorestaging.ieee.org/ielx7/48/9917395/09786553.pdf?arnumber=9786553

Reference152 articles.

1. Fast Target Detection in Synthetic Aperture Sonar Imagery: A New Algorithm and Large-Scale Performance Analysis

2. Coherence-Based Underwater Target Detection From Multiple Disparate Sonar Platforms

3. Target Localization in Synthetic Aperture Sonar Imagery using Convolutional Neural Networks

4. An automatic approach to the detection and extraction of mine features in sidescan sonar

5. Hybrid genetic optimization and statistical model based approach for the classification of shadow shapes in sonar imagery

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