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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/73085
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dc.contributor.authorPapa, João Paulo-
dc.contributor.authorGutierrez, Mario E. M.-
dc.contributor.authorNakamura, Rodrigo Y. M.-
dc.contributor.authorPapa, Luciene P.-
dc.contributor.authorVicentini, Irene Bastos Franceschini-
dc.contributor.authorVicentini, Carlos Alberto-
dc.date.accessioned2014-05-27T11:26:20Z-
dc.date.accessioned2016-10-25T18:36:22Z-
dc.date.available2014-05-27T11:26:20Z-
dc.date.available2016-10-25T18:36:22Z-
dc.date.issued2011-12-26-
dc.identifierhttp://dx.doi.org/10.1109/IEMBS.2011.6091259-
dc.identifier.citationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, p. 5084-5087.-
dc.identifier.issn1557-170X-
dc.identifier.urihttp://hdl.handle.net/11449/73085-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/73085-
dc.description.abstractThe spermatogenesis is crucial to the species reproduction, and its monitoring may shed light over some important information of such process. Thus, the germ cells quantification can provide useful tools to improve the reproduction cycle. In this paper, we present the first work that address this problem in fishes with machine learning techniques. We show here how to obtain high recognition accuracies in order to identify fish germ cells with several state-of-the-art supervised pattern recognition techniques. © 2011 IEEE.en
dc.format.extent5084-5087-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectAutomatic classification-
dc.subjectGerm cells-
dc.subjectMachine learning techniques-
dc.subjectRecognition accuracy-
dc.subjectSupervised pattern recognition-
dc.subjectPattern recognition-
dc.subjectCells-
dc.titleAutomatic classification of fish germ cells through optimum-path foresten
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionSouthwest Paulista College-
dc.description.affiliationDepartment of Computing Universidade Estadual Paulista (UNESP), Bauru-
dc.description.affiliationDepartment of Biological Sciences Universidade Estadual Paulista (UNESP), Bauru-
dc.description.affiliationSouthwest Paulista College, Avaré-
dc.description.affiliationUnespDepartment of Computing Universidade Estadual Paulista (UNESP), Bauru-
dc.description.affiliationUnespDepartment of Biological Sciences Universidade Estadual Paulista (UNESP), Bauru-
dc.identifier.doi10.1109/IEMBS.2011.6091259-
dc.identifier.wosWOS:000298810004007-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS-
dc.identifier.scopus2-s2.0-84055193445-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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