dc.contributor.author | French, Geoff | |
dc.contributor.author | Mackiewicz, Michal | |
dc.contributor.author | Fisher, Mark | |
dc.contributor.author | Holah, Helen | |
dc.contributor.author | Kilburn, Rachel | |
dc.contributor.author | Cambell, Neil | |
dc.contributor.author | Needle, Coby | |
dc.date.accessioned | 2019-11-21T08:47:15Z | |
dc.date.available | 2019-11-21T08:47:15Z | |
dc.date.created | 2019-11-20T14:23:12Z | |
dc.date.issued | 2019 | |
dc.identifier.issn | 1054-3139 | |
dc.identifier.uri | http://hdl.handle.net/11250/2629657 | |
dc.description.abstract | We report on the development of a computer vision system that analyses video from CCTV systems installed on fishing trawlers for the purpose of monitoring and quantifying discarded fish catch. Our system is designed to operate in spite of the challenging computer vision problem posed by conditions on-board fishing trawlers. We describe the approaches developed for isolating and segmenting individual fish and for species classification. We present an analysis of the variability of manual species identification performed by expert human observers and contrast the performance of our species classifier against this benchmark. We also quantify the effect of the domain gap on the performance of modern deep neural network-based computer vision systems. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | OXFORD Academic | nb_NO |
dc.title | Deep neural networks for analysis of fisheries surveillance video and automated monitoring of fish discards | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.rights.holder | © International Council for the Exploration of the Sea 2019. All rights reserved. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model. This authers Version is uploaded to the SINTEF repository, as a part of the SMARTFISH Project on Direct request of the Commission. The AAM is subject to embargo - and will be available for download once the embargo period has passed. | nb_NO |
dc.source.journal | ICES Journal of Marine Science | nb_NO |
dc.identifier.doi | 10.1093/icesjms/fsz149 | |
dc.identifier.cristin | 1749987 | |
dc.relation.project | EC/H2020/773521 | nb_NO |
cristin.unitcode | 7566,2,0,0 | |
cristin.unitname | Sjømatteknologi | |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |