Back to search

Article

Attentive CNN EEG or ACE-SeizNet: An Attention-Enhanced CNN Model for Automated EEG-Based Seizure Detection through Multi-Domain Deep Feature Fusion

2025-02-03

Abstract excerpt

<title>Abstract</title> <p>Background Epileptic seizure detection using electroencephalogram (EEG) signals is crucial for automated diagnosis and monitoring of neurological disorders. Traditional machine learning and deep learning models often face challenges in capturing subtle seizure patterns and maintaining high generalization across datasets. To address these limitations, this study proposes ACE-SeizNet, a...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
6e9b9c40-0727-531f-9559-8424f09158d6
DOI
10.21203/rs.3.rs-5935624/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Attentive CNN EEG or ACE-SeizNet: An Attention-Enhanced CNN Model for Automated EEG-Based Seizure Detection through Multi-Domain Deep Feature FusionDOI 10.21203/rs.3.rs-5935624/v1
Select a neighboring publication to make it the new centre.