Intestinal Parasites Classification Using Deep Belief Networks

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dc.contributor.authorRoder, Mateus [UNESP]
dc.contributor.authorPassos, Leandro A. [UNESP]
dc.contributor.authorRibeiro, Luiz Carlos Felix [UNESP]
dc.contributor.authorBenato, Barbara Caroline
dc.contributor.authorFalcão, Alexandre Xavier
dc.contributor.authorPapa, João Paulo [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)
dc.date.accessioned2022-05-01T01:25:44Z
dc.date.available2022-05-01T01:25:44Z
dc.date.issued2020-01-01
dc.description.abstractCurrently, approximately 4 billion people are infected by intestinal parasites worldwide. Diseases caused by such infections constitute a public health problem in most tropical countries, leading to physical and mental disorders, and even death to children and immunodeficient individuals. Although subjected to high error rates, human visual inspection is still in charge of the vast majority of clinical diagnoses. In the past years, some works addressed intelligent computer-aided intestinal parasites classification, but they usually suffer from misclassification due to similarities between parasites and fecal impurities. In this paper, we introduce Deep Belief Networks to the context of automatic intestinal parasites classification. Experiments conducted over three datasets composed of eggs, larvae, and protozoa provided promising results, even considering unbalanced classes and also fecal impurities.en
dc.description.affiliationSchool of Sciences São Paulo State University
dc.description.affiliationInstitute of Computing University of Campinas
dc.description.affiliationUnespSchool of Sciences São Paulo State University
dc.format.extent242-251
dc.identifierhttp://dx.doi.org/10.1007/978-3-030-61401-0_23
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 12415 LNAI, p. 242-251.
dc.identifier.doi10.1007/978-3-030-61401-0_23
dc.identifier.issn1611-3349
dc.identifier.issn0302-9743
dc.identifier.scopus2-s2.0-85096520555
dc.identifier.urihttp://hdl.handle.net/11449/233058
dc.language.isoeng
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.sourceScopus
dc.subjectData augmentation
dc.subjectDeep Belief Networks
dc.subjectIntestinal parasites
dc.subjectRestricted Boltzmann Machines
dc.titleIntestinal Parasites Classification Using Deep Belief Networksen
dc.typeTrabalho apresentado em evento
unesp.author.orcid0000-0002-3112-5290[1]
unesp.author.orcid0000-0003-3529-3109[2]
unesp.author.orcid0000-0003-1265-0273[3]
unesp.author.orcid0000-0003-0806-3607[4]
unesp.author.orcid0000-0002-2914-5380[5]
unesp.author.orcid0000-0002-6494-7514[6]
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Ciências, Baurupt
unesp.departmentComputação - FCpt

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