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Enhanced YOLOv8 Ship Detection Empower Unmanned Surface Vehicles for Advanced Maritime Surveillance

Abdelilah Haijoub1, Anas Hatim2, Antonio Guerrero-Gonzalez3

  • 1Engineering Sciences Laboratory, National School of Applied Sciences of Kenitra, Ibn Tofail University, Kenitra 14000, Morocco.

Journal of Imaging
|December 27, 2024
PubMed
Summary

This study introduces an AI system for detecting and tracking unmanned surface vehicles (USVs) using an enhanced YOLOv8 model. The system achieves high accuracy and speed with low energy consumption, advancing maritime surveillance capabilities.

Keywords:
YOLOV8 enhancementaccuracyedge devicesenergy efficiencymachine learningmaritime surveillanceunmanned surface vehicles

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