Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/9975
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dc.contributor.authorAli, Roznizaen_UK
dc.contributor.authorHussain, Amiren_UK
dc.contributor.authorBron, Jamesen_UK
dc.contributor.authorShinn, Andrewen_UK
dc.date.accessioned2016-12-08T22:18:54Z-
dc.date.available2016-12-08T22:18:54Z-
dc.date.issued2011-11en_UK
dc.identifier.urihttp://hdl.handle.net/1893/9975-
dc.description.abstractThis study explores the use of multi-stage machine learning based classifiers and feature selection techniques in the classification and identification of fish parasites. Accurate identification of pathogens is a key to their control and as a proof of concept, the monogenean worm genus Gyrodactylus, economically important pathogens of cultured fish species, an ideal test-bed for the selected techniques. Gyrodactylus salaris is a notifiable pathogen of salmonids and a semi-automated / automated method permitting its confident species discrimination from other non-pathogenic species is sought to assist disease diagnostics during periods of a suspected outbreak. This study will assist pathogen management in wild and cultured fish stocks, providing improvements in fish health and welfare and accompanying economic benefits. Multi-stage classification is proposed as a solution to this problem because use of a single classifier is not sufficient to ensure that all the species are accurately classified. The results show that Linear Discriminant Analysis (LDA) with 21 features is the best classifier for performing the initial classification of Gyrodactylus species. This first stage classification which allocates specimens to species-groups is then followed by a second or subsequent round of classification using additional classifiers to allocate species to their true class within the species-groups.en_UK
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.relationAli R, Hussain A, Bron J & Shinn A (2011) Multi-stage classification of Gyrodactylus species using machine learning and feature selection techniques. In: Proceedings of the 2011 11th International Conference on Intelligent Systems Design and Applications. ISDA 201111th International Conference on Intelligent Systems Design and Applications (ISDA), Cordoba, Spain, 22.11.2011-24.11.2011. Piscataway, NJ, USA: IEEE, pp. 457-462. http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6121698&abstractAccess=no&userType=inst; https://doi.org/10.1109/ISDA.2011.6121698en_UK
dc.relation.urihttp://www.uco.es/isda2011/en_UK
dc.rightsThe publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.en_UK
dc.rights.urihttp://www.rioxx.net/licenses/under-embargo-all-rights-reserveden_UK
dc.subjectGyrodactylusen_UK
dc.subjectfeature selectionen_UK
dc.subjectmachine learningen_UK
dc.subjectspecies classificationen_UK
dc.titleMulti-stage classification of Gyrodactylus species using machine learning and feature selection techniquesen_UK
dc.typeConference Paperen_UK
dc.rights.embargodate2999-12-31en_UK
dc.rights.embargoreason[Ali Amir Bron Shinn 2011.pdf] The publisher does not allow this work to be made publicly available in this Repository therefore there is an embargo on the full text of the work.en_UK
dc.identifier.doi10.1109/ISDA.2011.6121698en_UK
dc.citation.issn2164-7143en_UK
dc.citation.spage457en_UK
dc.citation.epage462en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.identifier.urlhttp://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6121698&abstractAccess=no&userType=insten_UK
dc.author.emailaps1@stir.ac.uken_UK
dc.citation.btitleProceedings of the 2011 11th International Conference on Intelligent Systems Design and Applicationsen_UK
dc.citation.conferencedates2011-11-22 - 2011-11-24en_UK
dc.citation.conferencelocationCordoba, Spainen_UK
dc.citation.conferencenameISDA 201111th International Conference on Intelligent Systems Design and Applications (ISDA)en_UK
dc.citation.isbn978-1-4577-1676-8en_UK
dc.publisher.addressPiscataway, NJ, USAen_UK
dc.contributor.affiliationUniversity of Stirlingen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.contributor.affiliationInstitute of Aquacultureen_UK
dc.contributor.affiliationInstitute of Aquacultureen_UK
dc.identifier.scopusid2-s2.0-84857519520en_UK
dc.identifier.wtid752381en_UK
dc.contributor.orcid0000-0002-8080-082Xen_UK
dc.contributor.orcid0000-0003-3544-0519en_UK
dc.contributor.orcid0000-0002-5434-2685en_UK
dcterms.dateAccepted2011-11-30en_UK
dc.date.filedepositdate2012-11-21en_UK
rioxxterms.typeConference Paper/Proceeding/Abstracten_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorAli, Rozniza|en_UK
local.rioxx.authorHussain, Amir|0000-0002-8080-082Xen_UK
local.rioxx.authorBron, James|0000-0003-3544-0519en_UK
local.rioxx.authorShinn, Andrew|0000-0002-5434-2685en_UK
local.rioxx.projectInternal Project|University of Stirling|https://isni.org/isni/0000000122484331en_UK
local.rioxx.freetoreaddate2999-12-31en_UK
local.rioxx.licencehttp://www.rioxx.net/licenses/under-embargo-all-rights-reserved||en_UK
local.rioxx.filenameAli Amir Bron Shinn 2011.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source978-1-4577-1676-8en_UK
Appears in Collections:Aquaculture Conference Papers and Proceedings

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