Human-assisted vs. deep learning feature extraction: an evaluation of ECG features extraction methods for arrhythmia classification using machine learning
The success of arrhythmia classification tasks with Machine Learning (ML) algorithms is based on the handcrafting extraction of features from Electrocardiography (ECG) signals. However, feature extraction is a time-consuming trial-and-error approach. Deep Neural Network (DNN) algorithms bypass the p...
| Autor principal: | |
|---|---|
| Outros Autores: | , , |
| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2022
|
| Assuntos: | |
| Texto completo: | https://hdl.handle.net/1822/80331 |
| País: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/80331 |