DenseNet-Based Classification of EEG Abnormalities Using Spectrograms
Electroencephalogram (EEG) analysis is essential for diagnosing neurological disorders but typically requires expert interpretation and significant time. Purpose: This study aims to automate the classification of normal and abnormal EEG recordings to support clinical diagnosis and reduce manual work...
Сохранить в:
| Главные авторы: | , |
|---|---|
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
MDPI AG
2025-08-01
|
| Серии: | Algorithms |
| Предметы: | |
| Online-ссылка: | https://www.mdpi.com/1999-4893/18/8/486 |
| Метки: |
Нет меток, Требуется 1-ая метка записи!
|