Publication:

A comprehensive review of datasets and deep learning techniques for vision in unmanned surface vehicles

Date

2025-AUG 1
Journal article
https://doi.org/10.1016/j.oceaneng.2025.121501
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dc.contributor.authorTrinh, Linh
dc.contributor.authorMercelis, Siegfried
dc.contributor.authorAnwar, Ali
dc.date.accessioned2025-06-06T04:50:10Z
dc.date.available2025-06-06T04:50:10Z
dc.date.issued2025-AUG 1
dc.description.wosFundingTextThe work was carried out in the framework of project INNO2MARE-Strengthening the Capacity for Excellence of Slovenian and Croatian Innovation Ecosystems to Support the Digital and Green Transitions of Maritime Regions (Funded by the European Union under the Horizon Europe Grant 101087348) .
dc.identifier.doi10.1016/j.oceaneng.2025.121501
dc.identifier.issn0029-8018
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/45762
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD
dc.source.journalOCEAN ENGINEERING
dc.source.numberofpages29
dc.source.volume334
dc.subject.keywordsOBJECT DETECTION
dc.subject.keywordsSEMANTIC SEGMENTATION
dc.subject.keywordsOBSTACLE DETECTION
dc.subject.keywordsSHIP DETECTION
dc.subject.keywordsNETWORK
dc.subject.keywordsCAMERA
dc.subject.keywordsRADAR
dc.subject.keywordsENVIRONMENT
dc.subject.keywordsTRACKING
dc.title

A comprehensive review of datasets and deep learning techniques for vision in unmanned surface vehicles

dc.typeJournal article
dspace.entity.typePublication
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