An hybrid cnn-transformer model based on multi-feature extraction and attention fusion mechanism for cerebral emboli classification
Résumé
When dealing with signal processing and deep learning for classification, the choice of inputting whether the raw signal or transforming it into a time-frequency representation (TFR) remains an open question. In this work, we propose a novel CNN-Transformer
Domaines
Informatique [cs]
Fichier principal
Vindas-22_MLHC_An hybrid CNN-Transformer model based on multi-feature.pdf (1000.33 Ko)
Télécharger le fichier
| Origine | Fichiers éditeurs autorisés sur une archive ouverte |
|---|