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dc.contributor.authorMyrum, Espen
dc.contributor.authorNørstebø, Simen Andre
dc.contributor.authorGeorge, Sony
dc.contributor.authorPedersen, Marius
dc.contributor.authorMuseth, Jon
dc.date.accessioned2020-02-04T12:14:49Z
dc.date.available2020-02-04T12:14:49Z
dc.date.created2019-12-05T11:20:42Z
dc.date.issued2019
dc.identifier.citationNIK: Norsk Informatikkonferanse. 2019, .nb_NO
dc.identifier.issn1892-0713
dc.identifier.urihttp://hdl.handle.net/11250/2639552
dc.description.abstractFish stocking is the method of raising fish in a hatchery and releasing them into a river or lake to sustain or increase an existing population or to create a population. This has been practised in many countries, including Norway. Before the fish are released, the adipose fin is commonly removed in order to identify that it is a stocked fish. Cameras have been mounted in several Norwegian rivers in order to monitor fish populations. Classification of fish from these cameras is today a manual task carried out by people. In this paper we propose an automatic classification method to separate wild fish from stocked fish using machine learning. Experiments on an image set of trouts (Salmo Trutta) show a very high accuracy of the proposed method.nb_NO
dc.language.isoengnb_NO
dc.publisherBibsys Open Journal Systemsnb_NO
dc.relation.urihttps://ojs.bibsys.no/index.php/NIK/article/view/638
dc.titleAn automatic image-based system for detecting wild and stocked fishnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber9nb_NO
dc.source.journalNIK: Norsk Informatikkonferansenb_NO
dc.identifier.cristin1757044
dc.description.localcodeThis paper was presented at the NIK-2019 conference; see http://www.nik.no/nb_NO
cristin.unitcode194,63,10,0
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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