Capsule neural network based approach for subject specific and cross-subjects seizure detection from EEG signals

The objective of this study is to propose an approach to detect Seizure and Non-Seizure phenomenon from the highly inconsistent and non-linear EEG signals. In the view of performing cross-subject classification over the inconsistency and non-linear characteristics of EEG signals, we have proposed a...

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Veröffentlicht in:	Multimedia tools and applications Jg. 82; H. 23; S. 35221 - 35252
Hauptverfasser:	Jana, Gopal Chandra, Swami, Keshav, Agrawal, Anupam
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.09.2023 Springer Nature B.V
Schlagworte:	Accuracy Artificial neural networks Classification Computer Communication Networks Computer Science Data Structures and Information Theory Datasets Decision trees Electroencephalography Multimedia Information Systems Neural networks Performance evaluation Special Purpose and Application-Based Systems Training Logistic regression Electroencephalogram (EEG) Capsule neural network Decision tree Convolutional neural network Cross-subject seizure detection
ISSN:	1380-7501, 1573-7721
Online-Zugang:	Volltext
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