Publicação:
Automatic classification of fish germ cells through optimum-path forest

dc.contributor.authorPapa, João Paulo [UNESP]
dc.contributor.authorGutierrez, Mario E. M. [UNESP]
dc.contributor.authorNakamura, Rodrigo Y. M. [UNESP]
dc.contributor.authorPapa, Luciene P.
dc.contributor.authorVicentini, Irene Bastos Franceschini [UNESP]
dc.contributor.authorVicentini, Carlos Alberto [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionSouthwest Paulista College
dc.date.accessioned2014-05-27T11:26:20Z
dc.date.available2014-05-27T11:26:20Z
dc.date.issued2011-12-26
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.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.format.extent5084-5087
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.doi10.1109/IEMBS.2011.6091259
dc.identifier.issn1557-170X
dc.identifier.lattes9039182932747194
dc.identifier.lattes9581468058921952
dc.identifier.lattes3150094336796923
dc.identifier.scopus2-s2.0-84055193445
dc.identifier.urihttp://hdl.handle.net/11449/73085
dc.identifier.wosWOS:000298810004007
dc.language.isoeng
dc.relation.ispartofProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
dc.rights.accessRightsAcesso aberto
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.typeTrabalho apresentado em evento
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dspace.entity.typePublication
unesp.author.lattes9039182932747194
unesp.author.lattes9581468058921952
unesp.author.lattes3150094336796923[6]
unesp.author.orcid0000-0002-6494-7514[4]
unesp.author.orcid0000-0002-6816-033X[6]
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Ciências, Baurupt
unesp.departmentCiências Biológicas - FCpt
unesp.departmentComputação - FCpt

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