Infrared Ship Detection Based on Improved YOLO-11

In the marine field, infrared detection technology is of great significance for timely localization and detection of ships in security missions. However, since infrared ship targets are often in the environmental conditions of small pixel occupancy, low contrast and complex background, it poses a gr...

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Bibliographic Details
Published inProceedings (International Confernce on Computational Intelligence and Communication Networks) pp. 928 - 932
Main Author Hu, Yayuan
Format Conference Proceeding
LanguageEnglish
Published IEEE 22.12.2024
Subjects
Attention mechanisms
Feature extraction
infrared target detection
Location awareness
Marine vehicles
Network architecture
Object detection
Reflection
Sea surface
Security
ship image
Surface waves
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ISSN2472-7555
DOI10.1109/CICN63059.2024.10847489

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Summary:In the marine field, infrared detection technology is of great significance for timely localization and detection of ships in security missions. However, since infrared ship targets are often in the environmental conditions of small pixel occupancy, low contrast and complex background, it poses a great challenge for multiship detection, classification, and localization tasks. Therefore, to solve these problems, we propose a lightweight enhanced small target infrared ship target detection (YOLO-FFE) network, Designed lightweight and efficient C2FFA module to increase the feature extraction capability of the backbone network. A lightweight attention mechanism, ELA, is added to the small-target detection header to better learn and predict the locations and bounding boxes of small targets in ship images. Experiments demonstrate that the proposed YOLO-FFE has better detection performance for infrared ship targets.
ISSN:2472-7555
DOI:10.1109/CICN63059.2024.10847489