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Future trends in optimum-path forest classification

dc.contributor.authorPapa, João Paulo [UNESP]
dc.contributor.authorFalcão, Alexandre Xavier
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)
dc.date.accessioned2023-03-02T08:37:56Z
dc.date.available2023-03-02T08:37:56Z
dc.date.issued2022-01-24
dc.description.abstractIn the past years, we have observed an increasing number of applications that require machine learning techniques to sort out problems that are not straightforward to humans. The reasons vary from information that is not clearly visible to the human eye (e.g., microscopic patterns in medical images) or the massive amount of data to analyze. This book aimed to shed light on the Optimum-Path Forest framework, which comprises approaches to dealing with supervised, semi-supervised, and unsupervised learning. Different applications have been presented together with a theoretical background concerning the techniques presented here. We expect to call the attention and curiosity of the readers towards OPF-based techniques and their strengths. © 2022 Copyrighten
dc.description.affiliationUNESP - São Paulo State University School of Sciences
dc.description.affiliationDepartment of Computing São Paulo State University
dc.description.affiliationInstitute of Computing University of Campinas (UNICAMP) Campinas
dc.description.affiliationUnespUNESP - São Paulo State University School of Sciences
dc.description.affiliationUnespDepartment of Computing São Paulo State University
dc.format.extent217-219
dc.identifierhttp://dx.doi.org/10.1016/B978-0-12-822688-9.00017-7
dc.identifier.citationOptimum-Path Forest: Theory, Algorithms, and Applications, p. 217-219.
dc.identifier.doi10.1016/B978-0-12-822688-9.00017-7
dc.identifier.scopus2-s2.0-85134954561
dc.identifier.urihttp://hdl.handle.net/11449/242086
dc.language.isoeng
dc.relation.ispartofOptimum-Path Forest: Theory, Algorithms, and Applications
dc.sourceScopus
dc.subjectClustering
dc.subjectDeep learning
dc.subjectMachine learning
dc.subjectOptimum-path forest
dc.subjectSupervised learning
dc.titleFuture trends in optimum-path forest classificationen
dc.typeCapítulo de livro
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Ciências, Baurupt
unesp.departmentComputação - FCpt

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