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Body surface potential mapping time series recognition using convolutional and recurrent neural networks

cris.lastimport.scopus2024-09-17T01:31:24Z
dc.abstract.enThis article shows recognition of biomedical time series from Body Surface Potential Mapping by means of different convolutional and recurrent neural networks models. The various kinds of neural networks models were examined and compared: model with 1D convolutional layer, model with Long - Short Term Memory layer and model with Gated Recurrent Unit layer.
dc.affiliationTransportu i Informatyki
dc.contributor.authorTomasz Rymarczyk
dc.contributor.authorDariusz Wójcik
dc.contributor.authorŁ Maciura
dc.contributor.authorW Rosa
dc.contributor.authorM Bartosik
dc.date.accessioned2024-08-05T07:08:09Z
dc.date.available2024-08-05T07:08:09Z
dc.date.issued2022
dc.identifier.doi10.1088/1742-6596/2408/1/012001
dc.identifier.eissn1742-6596
dc.identifier.issn1742-6588
dc.identifier.urihttps://repo.akademiawsei.eu/handle/item/560
dc.languageen
dc.pbn.affiliationinformation and communication technology
dc.relation.ispartofJournal of Physics: Conference Series
dc.rightsCC-BY
dc.subject.enbody surface
dc.subject.enpotential mapping time
dc.subject.enconvolutinal and recurrent neural networks
dc.subject.enneural networks
dc.titleBody surface potential mapping time series recognition using convolutional and recurrent neural networks
dc.typeReviewArticleConference
dspace.entity.typePublication
oaire.citation.issue1
oaire.citation.volume2408