Name
Abstract | ||
|---|---|---|
•Stacked Autoencoders are very efficient in encoding QRS waves.•Automatic features are extracted from ECG by deep neural network architecture.•The developed architecture for QRS detection is comparable to state-of-the-art algorithms on many datasets.•The proposed method outperforms all deep neural networks in terms of execution time. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.eswa.2021.115528 | Expert Systems with Applications |
Keywords | DocType | Volume |
ECG,Deep learning,Stacked autoencoder,QRS detection | Journal | 184 |
ISSN | Citations | PageRank |
0957-4174 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohamed Amine Belkadi | 1 | 0 | 0.34 |
| Abdelhamid Daamouche | 2 | 52 | 3.88 |
| Farid Melgani | 3 | 1100 | 80.98 |