Enhanced YOLOv8 Ship Detection Empower Unmanned Surface Vehicles for Advanced Maritime Surveillance
Enhanced YOLOv8 Ship Detection Empower Unmanned Surface Vehicles for Advanced Maritime Surveillance
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Publisher
Switzerland: MDPI AG
Journal title
Language
English
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Publisher
Switzerland: MDPI AG
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Contents
The evolution of maritime surveillance is significantly marked by the incorporation of Artificial Intelligence and machine learning into Unmanned Surface Vehicles (USVs). This paper presents an AI approach for detecting and tracking unmanned surface vehicles, specifically leveraging an enhanced version of YOLOv8, fine-tuned for maritime surveillanc...
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Full title
Enhanced YOLOv8 Ship Detection Empower Unmanned Surface Vehicles for Advanced Maritime Surveillance
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_a216223cc42c4040a0928a369de12bda
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_a216223cc42c4040a0928a369de12bda
Other Identifiers
ISSN
2313-433X
E-ISSN
2313-433X
DOI
10.3390/jimaging10120303
