Deep Learning for COPD Analysis Using Lung Sounds
dc.contributor.author | ALLAHVERDİ, Novruz | |
dc.contributor.author | ALTAN, Gökhan | |
dc.contributor.author | KUTLU, Yakup | |
dc.date.accessioned | 2019-07-10T08:12:01Z | |
dc.date.available | 2019-07-10T08:12:01Z | |
dc.date.issued | 2018-07 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12498/1026 | |
dc.description.abstract | Deep Learning(DL) algotithms have become popular with the detailed analyzing capabilities with many hidden layers in recent years. The size of hidden layer in the classifier models is complately correlated with the analyzing capability of the proposed mode. Multiple hidden layers and neuron size in the hidden layers enhance the analyzing capability of the models,whereas increasing the training time. | |
dc.language.iso | en | en_US |
dc.subject | Deep Learning | en_US |
dc.subject | Deep Belief Networks | en_US |
dc.subject | Hibert-Huang Transform | en_US |
dc.title | Deep Learning for COPD Analysis Using Lung Sounds | en_US |
dc.type | Konferans Bildirisi | en_US |