Intestinal Parasites Classification Using Deep Belief Networks

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversidade Estadual de Campinas (UNICAMP)-
Autor(es): dc.creatorRoder, Mateus-
Autor(es): dc.creatorPassos, Leandro A.-
Autor(es): dc.creatorRibeiro, Luiz Carlos Felix-
Autor(es): dc.creatorBenato, Barbara Caroline-
Autor(es): dc.creatorFalcão, Alexandre Xavier-
Autor(es): dc.creatorPapa, João Paulo-
Data de aceite: dc.date.accessioned2025-08-21T21:21:42Z-
Data de disponibilização: dc.date.available2025-08-21T21:21:42Z-
Data de envio: dc.date.issued2022-05-01-
Data de envio: dc.date.issued2022-05-01-
Data de envio: dc.date.issued2019-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/978-3-030-61401-0_23-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/233058-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/233058-
Descrição: dc.descriptionCurrently, 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.-
Descrição: dc.descriptionSchool of Sciences São Paulo State University-
Descrição: dc.descriptionInstitute of Computing University of Campinas-
Descrição: dc.descriptionSchool of Sciences São Paulo State University-
Formato: dc.format242-251-
Idioma: dc.languageen-
Relação: dc.relationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectData augmentation-
Palavras-chave: dc.subjectDeep Belief Networks-
Palavras-chave: dc.subjectIntestinal parasites-
Palavras-chave: dc.subjectRestricted Boltzmann Machines-
Título: dc.titleIntestinal Parasites Classification Using Deep Belief Networks-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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