Implementation of deep neural networks for classifying electroencephalogram signal using fractional S‐transform for epileptic seizure detection-Reference-Cited by-同舟云学术

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Implementation of deep neural networks for classifying electroencephalogram signal using fractional S‐transform for epileptic seizure detection

Published:2021-03-02 Issue:2 Volume:31 Page:895-908
ISSN:0899-9457
Container-title:International Journal of Imaging Systems and Technology
language:en
Short-container-title:Int J Imaging Syst Technol

Author:

Ashokkumar S. R.¹^ORCID,Anupallavi S.²^ORCID,Premkumar M.³,Jeevanantham V.³^ORCID

Affiliation:

1. Department of Electronics and Communication Engineering Sri Eshwar College of Engineering Coimbatore Tamil Nadu India

2. Department of Electronics and Communication Engineering VSB College of Engineering Technical Campus Coimbatore Tamil Nadu India

3. Department of Electronics and Communications Engineering SSM Institute of Engineering and Technology, Dindigul Coimbatore Tamil Nadu India

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Software,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ima.22565

Reference30 articles.

1. An accurate sleep stages classification system using a new class of optimally time-frequency localized three-band wavelet filter bank

2. A new approach to characterize epileptic seizures using analytic time-frequency flexible wavelet transform and fractal dimension

3. Combining STFT and Random Forest Algorithm for Epileptic Detection

4. Epileptic Seizure Detection in EEGs Using Time–Frequency Analysis

5. Localization of the complex spectrum: the S transform

Cited by 36 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Integrated TSVM-TSK fusion for enhanced EEG-based epileptic seizure detection: Robust classifier with competitive learning;Biomedical Signal Processing and Control;2024-10

2. GoldenFish Sentinel feature selection with SBM classifier for automatic seizure detection from EEG data;Biomedical Signal Processing and Control;2024-09

3. Landscape of epilepsy research: Analysis and future trajectory;Interdisciplinary Neurosurgery;2024-06

4. Seizure Detection Based on Lightweight Inverted Residual Attention Network;International Journal of Neural Systems;2024-05-31

5. Retraction: “Implementation of deep neural networks for classifying electroencephalogram signal using fractional S‐transform for epileptic seizure detection”;International Journal of Imaging Systems and Technology;2024-03

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