Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/16513
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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.contributor.editorHuang, Ten_UK
dc.contributor.editorZeng, Zen_UK
dc.contributor.editorLi, Cen_UK
dc.contributor.editorLeung, CSen_UK
dc.date.accessioned2013-08-24T00:00:14Z-
dc.date.available2013-08-24T00:00:14Zen_UK
dc.date.issued2012en_UK
dc.identifier.urihttp://hdl.handle.net/1893/16513-
dc.description.abstractActive Shape Models (ASM) are applied to the attachment hooks of several species of Gyrodactylus, including the notifiable pathogen G. salaris, to classify each species to their true species type. ASM is used as a feature extraction tool to select information from hook images that can be used as input data into trained classifiers. Linear (i.e. LDA and KNN) and non-linear (i.e. MLP and SVM) models are used to classify Gyrodactylus species. Species of Gyrodactylus, ectoparasitic monogenetic flukes of fish, are difficult to discriminate and identify on morphology alone and their speciation currently requires taxonomic expertise. The current exercise sets out to confidently classify species, which in this example includes a species which is notifiable pathogen of Atlantic salmon, to their true class with a high degree of accuracy. The findings from the current exercise demonstrates that data subsequently imported into a K-NN classifier, outperforms several other methods of classification (i.e. LDA, MLP and SVM) that were assessed, with an average classification accuracy of 98.75%.en_UK
dc.language.isoenen_UK
dc.publisherSpringeren_UK
dc.relationAli R, Hussain A, Bron J & Shinn A (2012) The use of ASM feature extraction and machine learning for the discrimination of members of the fish ectoparasite genus gyrodactylus. In: Huang T, Zeng Z, Li C & Leung C (eds.) Neural Information Processing: 19th International Conference, ICONIP 2012, Doha, Qatar, November 12-15, 2012, Proceedings, Part IV. Lecture Notes in Computer Science, 7666. Berlin Heidelberg: Springer, pp. 256-263. http://link.springer.com/chapter/10.1007/978-3-642-34478-7_32#; https://doi.org/10.1007/978-3-642-34478-7_32en_UK
dc.relation.ispartofseriesLecture Notes in Computer Science, 7666en_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.subjectAttachment hooksen_UK
dc.subjectimage processingen_UK
dc.subjectSEMen_UK
dc.subjectparasiteen_UK
dc.subjectmachine learning classifieren_UK
dc.titleThe use of ASM feature extraction and machine learning for the discrimination of members of the fish ectoparasite genus gyrodactylusen_UK
dc.typePart of book or chapter of booken_UK
dc.rights.embargodate3000-12-01en_UK
dc.rights.embargoreason[Use of ASM Feature Extraction and Machine.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.doi10.1007/978-3-642-34478-7_32en_UK
dc.citation.issn0302-9743en_UK
dc.citation.spage256en_UK
dc.citation.epage263en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.identifier.urlhttp://link.springer.com/chapter/10.1007/978-3-642-34478-7_32#en_UK
dc.author.emailamir.hussain@stir.ac.uken_UK
dc.citation.btitleNeural Information Processing: 19th International Conference, ICONIP 2012, Doha, Qatar, November 12-15, 2012, Proceedings, Part IVen_UK
dc.citation.isbn978-3-642-34477-0en_UK
dc.publisher.addressBerlin Heidelbergen_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-s2.0-84869025511en_UK
dc.identifier.wtid721004en_UK
dc.contributor.orcid0000-0002-8080-082Xen_UK
dc.contributor.orcid0000-0003-3544-0519en_UK
dc.contributor.orcid0000-0002-5434-2685en_UK
dcterms.dateAccepted2012-12-31en_UK
dc.date.filedepositdate2013-08-08en_UK
rioxxterms.typeBook chapteren_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.contributorHuang, T|en_UK
local.rioxx.contributorZeng, Z|en_UK
local.rioxx.contributorLi, C|en_UK
local.rioxx.contributorLeung, CS|en_UK
local.rioxx.freetoreaddate3000-12-01en_UK
local.rioxx.licencehttp://www.rioxx.net/licenses/under-embargo-all-rights-reserved||en_UK
local.rioxx.filenameUse of ASM Feature Extraction and Machine.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source978-3-642-34477-0en_UK
Appears in Collections:Computing Science and Mathematics Book Chapters and Sections

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