dc.contributor.author | Ren, Guangyu | |
dc.contributor.author | Dai, Tianhong | |
dc.contributor.author | Barmpoutis, Panagiotis | |
dc.contributor.author | Stathaki, Tania | |
dc.date.accessioned | 2023-02-24T14:41:01Z | |
dc.date.available | 2023-02-24T14:41:01Z | |
dc.date.issued | 2020-10-16 | |
dc.identifier.citation | Ren , 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/electronics9101702 | en |
dc.identifier.issn | 2079-9292 | |
dc.identifier.other | PURE: 221357986 | |
dc.identifier.other | PURE UUID: 710edf83-74d0-4a4d-93e0-8381aafd225e | |
dc.identifier.other | ORCID: /0000-0001-8904-1551/work/122287656 | |
dc.identifier.uri | https://hdl.handle.net/2164/20162 | |
dc.description | Funding 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.extent | 13 | |
dc.language.iso | eng | |
dc.relation.ispartof | Electronics (Switzerland) | en |
dc.rights | This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | en |
dc.subject | salient object detection | en |
dc.subject | pyramid self-attention module | en |
dc.subject | fully convolution network | en |
dc.subject | feature pyramid network | en |
dc.subject | QA75 Electronic computers. Computer science | en |
dc.subject | European Commission | en |
dc.subject | 691218 | en |
dc.subject | EU H2020 TERPSICHORE project | en |
dc.subject | Supplementary Information | en |
dc.subject.lcc | QA75 | en |
dc.title | Salient Object Detection Combining a Self-Attention Module and a Feature Pyramid Network | en |
dc.type | Journal article | en |
dc.contributor.institution | University of Aberdeen.Machine Learning | en |
dc.contributor.institution | University of Aberdeen.Computing Science | en |
dc.description.status | Peer reviewed | en |
dc.description.version | Publisher PDF | en |
dc.identifier.doi | https://doi.org/10.3390/electronics9101702 | |
dc.identifier.url | https://github.com/ic-qialanqian/PSAMNet | en |
dc.identifier.vol | 9 | en |
dc.identifier.iss | 10 | en |