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dc.contributor.authorWaszak, Maryna
dc.contributor.authorCardaillac, Alexandre
dc.contributor.authorElvesæter, Brian
dc.contributor.authorRødølen, Frode
dc.contributor.authorLudvigsen, Martin
dc.date.accessioned2023-01-03T13:27:26Z
dc.date.available2023-01-03T13:27:26Z
dc.date.issued2022-12-23
dc.description.abstractIn this article, we present the first large-scale data set for underwater ship lifecycle inspection, analysis and condition information (LIACI). It contains 1893 images with pixel annotations for ten object categories: defects, corrosion, paint peel, marine growth, sea chest gratings, overboard valves, propeller, anodes, bilge keel and ship hull. The images have been collected during underwater ship inspections and annotated by human domain experts. We also present a benchmark evaluation of state-of-the-art semantic segmentation approaches based on standard performance metrics. Consequently, we propose to use U-Net with a MobileNetV2 backbone for the segmentation task due to its balanced tradeoff between performance and computational efficiency, which is essential if used for real-time evaluation. Also, we demonstrate its benefits for in-water inspections by providing quantitative evaluations of the inspection findings. With a variety of use cases, the proposed segmentation pipeline and the LIACI data set create new promising opportunities for future research in underwater ship inspections.en_US
dc.identifier.citationWaszak, Cardaillac, Elvesæter, Rødølen, Ludvigsen. Semantic Segmentation in Underwater Ship Inspections: Benchmark and Dataset. IEEE Journal of Oceanic Engineering. 2022
dc.identifier.cristinIDFRIDAID 2071613
dc.identifier.doi10.1109/JOE.2022.3219129
dc.identifier.issn0364-9059
dc.identifier.issn1558-1691
dc.identifier.urihttps://hdl.handle.net/10037/28006
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.journalIEEE Journal of Oceanic Engineering
dc.relation.projectIDNorges forskningsråd: 317854
dc.rights.holderCopyright 2022 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titleSemantic Segmentation in Underwater Ship Inspections: Benchmark and Dataseten_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 4.0 International (CC BY 4.0)
Med mindre det står noe annet, er denne innførselens lisens beskrevet som Attribution 4.0 International (CC BY 4.0)