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...

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Bibliographic Details

Published in:	Algorithms
Main Authors:	Lan Wei, Catherine Mooney
Format:	Article
Language:	English
Published:	MDPI AG 2025-08-01
Subjects:	EEG spectrogram DenseNet121 explainable automated classification
Online Access:	https://www.mdpi.com/1999-4893/18/8/486