Underwater Side-Scan Sonar Target Detection: An Enhanced YOLOv11 Framework Integrating Attention Mechanisms and a Bi-Directional Feature Pyramid Network

Underwater Side-Scan Sonar Target Detection: An Enhanced YOLOv11 Framework Integrating Attention Mechanisms and a Bi-Directional Feature Pyramid Network

Underwater target detection is pivotal for marine exploration, yet it faces significant challenges because of the inherent complex underwater environment. Sonar images are generally degraded by noise, exhibit low resolution, and lack prominent target features, making the extraction of useful feature...

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Bibliographic Details
Main Authors: Junhui Zhu, Houpu Li, Min Liu, Guojun Zhai, Shaofeng Bian, Ye Peng, Lei Liu
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Journal of Marine Science and Engineering
Subjects:
target detection
side-scan sonar
deep learning
bi-directional feature pyramid network
attention module
Online Access:https://www.mdpi.com/2077-1312/13/5/926
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