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Cited by 258Underwater Acoustics ResearchAdvanced Neural Network ApplicationsUnderwater Vehicles and Communication Systems

Real-Time Underwater Maritime Object Detection in Side-Scan Sonar Images Based on Transformer-YOLOv5

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Yu, Yongcan, Zhao, Jianhu, Gong, Quanhua, Huang, Chao, Zheng, Gen, Ma, Jinye·2021·Remote Sensing
DOI 10.3390/rs13183555
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Abstract

To overcome the shortcomings of the traditional manual detection of underwater targets in side-scan sonar (SSS) images, a real-time automatic target recognition (ATR) method is proposed in this paper. This method consists of image preprocessing, sampling, ATR by integration of the transformer module and YOLOv5s (that is, TR–YOLOv5s), and target localization. By considering the target-sparse and feature-barren characteristics of SSS images, a novel TR–YOLOv5s network and a down-sampling principle are put forward, and the attention mechanism is introduced in the method to meet the requirements of accuracy and efficiency for underwater target recognition. Experiments verified the proposed method achieved 85.6% mean average precision (mAP) and 87.8% macro-F2 score, and brought 12.5% and 10.6% gains compared with the YOLOv5s network trained from scratch, and had the real-time recognition speed of about 0.068 s per image.

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  • A real-time automatic target recognition method combining a transformer attention mechanism and the YOLOv5s model, named TR-YOLOv5s, was applied to side-scan sonar images.

    “Side-scan sonar images were used as inputs to a real-time automatic target recognition (ATR) method that applied a combination of a transformer attention mechanism [138] and the YOLOv5s model [133], named TR–YOLOv5s.”

    From A Survey of Underwater Acoustic Data Classification Methods Using Deep Learning for Shoreline Surveillance (2022) · cites this paper as [133]

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Research works printed but not linked: 31

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Cited by

Sorted by citations

Authors
Yu, Y., Zhao, J., Gong, Q., Huang, C., Zheng, G., & Ma, J.
Affiliations
  • Wuhan University (CN)
  • China Communications Construction Company (China) (CN)
Corresponding author
Zhao, Jianhu
ORCID
Venue
Remote Sensing
Publisher
MDPI AG
Published
2021-09-07
Volume
13
Issue
18
Pages
3555
ISSN
2072-4292 (ISSN-L)
DOI
10.3390/rs13183555
OpenAlex
W3197086755
Cited by
258
References
1
Citations by year
2026: 42 · 2025: 55 · 2024: 60 · 2023: 62 · 2022: 36 · 2021: 3
FWCI
19.37
Type
journal article
Language
en
Open access
Licence
Locations
  • Remote Sensing (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Natural Science Foundation of China (41576107, 41376109)
  • National Key R&D Program of China (2016YFB0501703)
Topics
  • Physical Sciences › Earth and Planetary Sciences › Oceanography › Underwater Acoustics Research
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
  • Physical Sciences › Engineering › Ocean Engineering › Underwater Vehicles and Communication Systems
Keywords
underwater object detection, side-scan sonar images, automatic target recognition, YOLOv5, attention mechanism, real-time detection, target localization, image downscaling, maritime target detection

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