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Salient Object Detection Combining a Self-Attention Module and a Feature Pyramid Network

dc.contributor.authorRen, Guangyu
dc.contributor.authorDai, Tianhong
dc.contributor.authorBarmpoutis, Panagiotis
dc.contributor.authorStathaki, Tania
dc.date.accessioned2024-02-07T08:55:12Z
dc.date.available2024-02-07T08:55:12Z
dc.date.issued2020-10-16
dc.identifier221357986
dc.identifier710edf83-74d0-4a4d-93e0-8381aafd225e
dc.identifier.citationRen , G , Dai , T , Barmpoutis , P & Stathaki , T 2020 , ' Salient Object Detection Combining a Self-Attention Module and a Feature Pyramid Network ' , Electronics (Switzerland) , vol. 9 , no. 10 , 1702 . https://doi.org/10.3390/electronics9101702en
dc.identifier.issn2079-9292
dc.identifier.otherORCID: /0000-0001-8904-1551/work/122287656
dc.identifier.urihttp://aura-test.abdn.ac.uk/handle/2164/20162
dc.descriptionFunding This research was funded by the EU H2020 TERPSICHORE project “Transforming Intangible Folkloric Performing Arts into Tangible Choreographic Digital Objects” under the grant agreement 691218.en
dc.format.extent13
dc.format.extent2995817
dc.language.isoeng
dc.relation.ispartofElectronics (Switzerland)en
dc.subjectsalient object detectionen
dc.subjectpyramid self-attention moduleen
dc.subjectfully convolution networken
dc.subjectfeature pyramid networken
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectEuropean Commissionen
dc.subject691218en
dc.subjectEU H2020 TERPSICHORE projecten
dc.subjectSupplementary Informationen
dc.subject.lccQA75en
dc.titleSalient Object Detection Combining a Self-Attention Module and a Feature Pyramid Networken
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Machine Learningen
dc.contributor.institutionUniversity of Aberdeen.Computing Scienceen
dc.description.statusPeer revieweden
dc.identifier.doihttps://doi.org/10.3390/electronics9101702
dc.identifier.urlhttps://github.com/ic-qialanqian/PSAMNeten
dc.identifier.vol9en
dc.identifier.iss10en


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