Multimodal Convolutional Deep Belief Networks for Stroke Classification with Fourier Transform

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorThe University of Manchester-
Autor(es): dc.creatorRoder, Mateus-
Autor(es): dc.creatorGomes, Nicolas-
Autor(es): dc.creatorYoshida, Arissa-
Autor(es): dc.creatorPapa, Joao Paulo-
Autor(es): dc.creatorCosten, Fumie-
Data de aceite: dc.date.accessioned2025-08-21T19:36:29Z-
Data de disponibilização: dc.date.available2025-08-21T19:36:29Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2022-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/SIBGRAPI59091.2023.10347165-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/307520-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/307520-
Descrição: dc.descriptionSeveral studies have investigated the vast potential of deep learning techniques in addressing a wide range of applications, from recommendation systems and service-based analysis to medical diagnosis. However, even with the remarkable results achieved in some computer vision tasks, there is still a vast scope for exploration. Over the past decade, various studies focused on developing automated medical systems to support diagnosis. Nevertheless, detecting cerebrovascular accidents remains a challenging task. In this regard, one way to improve these approaches is to incorporate information fusion techniques in deep learning architectures. This paper proposes a novel approach to enhance stroke classification by combining multimodal data from Fourier transform with Convolutional Deep Belief Networks. As the main result, the proposed approach achieved state-of-the-art results with an accuracy of 99.94%, demonstrating its effectiveness and potential for future applications.-
Descrição: dc.descriptionSão Paulo State University (UNESP) Computing Department-
Descrição: dc.descriptionSchool of Electrical and Electronic Engineering The University of Manchester-
Descrição: dc.descriptionSão Paulo State University (UNESP) Computing Department-
Formato: dc.format163-168-
Idioma: dc.languageen-
Relação: dc.relationBrazilian Symposium of Computer Graphic and Image Processing-
???dc.source???: dc.sourceScopus-
Título: dc.titleMultimodal Convolutional Deep Belief Networks for Stroke Classification with Fourier Transform-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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