Pattern recognition with applications to pre-diagnosis of pathologies in the vocal tract

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorSolgon Bassi, Regiane Denise-
Autor(es): dc.creatorDezani, Henrique-
Autor(es): dc.creatorSilva Paulo, Kátia Cristina-
Autor(es): dc.creatorCapobianco Guido, Rodrigo-
Autor(es): dc.creatorNunes da Silva, Ivan-
Autor(es): dc.creatorMarranghello, Norian-
Data de aceite: dc.date.accessioned2025-08-21T19:59:12Z-
Data de disponibilização: dc.date.available2025-08-21T19:59:12Z-
Data de envio: dc.date.issued2022-05-02-
Data de envio: dc.date.issued2022-05-02-
Data de envio: dc.date.issued2015-01-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1201/b18660-143-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/234382-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/234382-
Descrição: dc.descriptionFor the detection of laryngeal pathologies, in general medical examinations, for example laryngoscopy and stroboscopy, are adopted. Besides being considered invasive and uncomfortable procedures, they are made only by medical request when the diseases are already on advanced levels. In order to perform a computational pre-diagnosis of such conditions, this paper presents a non-invasive technique in which three classifiers are tested and compared: Euclidian distance, RBF Neural Network with the Gaussian kernel, and RBF Neural Network with the modified Gaussian kernel. Based on a database of normal and pathological voices, tests that demonstrate the effectiveness of the proposed technique, which can be implemented in real-time, were performed.-
Descrição: dc.descriptionUniversity of São Paulo-
Descrição: dc.descriptionNorth of São Paulo University-
Descrição: dc.descriptionSão Paulo State University-
Descrição: dc.descriptionSão Paulo State University-
Formato: dc.format645-648-
Idioma: dc.languageen-
Relação: dc.relationNetwork Security and Communication Engineering - Proceedings of the 2014 International Conference on Network Security and Communication Engineering, NSCE 2014-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectEuclidian distance-
Palavras-chave: dc.subjectLarynx pathologies-
Palavras-chave: dc.subjectRBF neural networks-
Palavras-chave: dc.subjectSignal processing-
Título: dc.titlePattern recognition with applications to pre-diagnosis of pathologies in the vocal tract-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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