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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/25750
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dc.contributor.authorXia, R-
dc.contributor.authorLi, G-
dc.contributor.authorHuang, Z-
dc.contributor.authorMeng, H-
dc.contributor.authorPang, Y-
dc.date.accessioned2023-01-08T12:30:41Z-
dc.date.available2023-01-08T12:30:41Z-
dc.date.issued2022-12-01-
dc.identifierORCID iDs: Ruiyang Xia https://orcid.org/0000-0002-2421-9512; Zhengwen Huang https://orcid.org/0000-0003-2426-242X; Hongying Meng https://orcid.org/0000-0002-8836-1382.-
dc.identifier.citationXia, R. et al. (2023) 'Bi-path Combination YOLO for Real-time Few-shot Object Detection', Pattern Recognition Letters, 165, pp. 91 - 97. doi: 10.1016/j.patrec.2022.11.025.en_US
dc.identifier.issn0167-8655-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/25750-
dc.description.sponsorshipNational Natural Science Foundation of China (No. 61971079); Brunel University London BREIF Award (No. 11937115); National Key Research and Development Program of China (No. 2019YFC1511300); Basic Research and Frontier Exploration Project of Chongqing (No. cstc2019jcyj-msxmX0666); Innovative Group Project of the National Natural Science Foundation of Chongqing (No. cstc2020jcyj-cxttX0002).en_US
dc.format.extent91 - 97-
dc.format.mediumPrint-Electronic-
dc.languageEnglish-
dc.language.isoen_USen_US
dc.publisherElsevieren_US
dc.rightsCopyright © 2022 Elsevier B.V. All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1016/j.patrec.2022.11.025, made available on this repository under a Creative Commons CC BY-NC-ND attribution licence (https://creativecommons.org/licenses/by-nc-nd/4.0/).-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.subjectfew-shot object detectionen_US
dc.subjecttransfer learningen_US
dc.subjectreal-timeen_US
dc.subjectbi-path combinationen_US
dc.subjectYou Only Look Onceen_US
dc.subjectAttentive DropBlocken_US
dc.titleBi-path Combination YOLO for Real-time Few-shot Object Detectionen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1016/j.patrec.2022.11.025-
dc.relation.isPartOfPattern Recognition Letters-
pubs.publication-statusPublished-
pubs.volume165-
dc.identifier.eissn1872-7344-
dc.rights.holderElsevier B.V.-
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