Introducing Region Based Pooling for handling a varied number of EEG channels for deep learning models

Introducing Region Based Pooling for handling a varied number of EEG channels for deep learning models

IntroductionA challenge when applying an artificial intelligence (AI) deep learning (DL) approach to novel electroencephalography (EEG) data, is the DL architecture's lack of adaptability to changing numbers of EEG channels. That is, the number of channels cannot vary neither in the training da...

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Bibliographic Details
Main Authors: Thomas Tveitstøl, Mats Tveter, Ana S. Pérez T., Christoffer Hatlestad-Hall, Anis Yazidi, Hugo L. Hammer, Ira R. J. Hebold Haraldsen
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-01-01
Series:Frontiers in Neuroinformatics
Subjects:
EEG
deep learning
machine learning
cross-dataset
cross-channel system
convolutional neural networks
Online Access:https://www.frontiersin.org/articles/10.3389/fninf.2023.1272791/full

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https://www.frontiersin.org/articles/10.3389/fninf.2023.1272791/full

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