A hybrid optimization-enhanced 1D-ResCNN framework for epileptic spike detection in scalp EEG signals

Abstract In order to detect epileptic spikes, this paper suggests a deep learning architecture that blends 1D residual convolutional neural networks (1D-ResCNN) with a hybrid optimization strategy. The Layer-wise Adaptive Moments (LAMB) and AdamW algorithms have been used in the model’s optimization...

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Bibliographic Details
Main Authors: Priyaranjan Kumar, Prabhat Kumar Upadhyay
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-025-90164-3
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