An Efficient CADNet for Classification of High-frequency Oscillations in Magnetoencephalography-Reference-Cited by-同舟云学术

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An Efficient CADNet for Classification of High-frequency Oscillations in Magnetoencephalography

Published:2022-09-25 Issue: Volume: Page:
ISSN:
Container-title:2022 4th International Conference on Robotics and Computer Vision (ICRCV)
language:
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Author:

Zhang Meijuan¹,Liu Jun¹,Liu Chuang¹,Wu Ting²,Peng Xueping³

Affiliation:

1. Hubei Key Laboratory of Intelligent Robot (Wuhan Institute of Technology),School of Computer Science and Engineering, Wuhan Institute of Technology,Wuhan,China

2. Nanjing Brain Hospital, Nanjing Medical University,Department of Neurology,Nanjing,China

3. University of Technology Sydney,Australia

Funder

National Natural Science Foundation of China

Innovation Fund

Ministry of Education

Technology Development

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9953195/9953171/09953255.pdf?arnumber=9953255

Reference18 articles.

1. MEG detection of high frequency oscillations and intracranial-EEG validation in pediatric epilepsy surgery

2. Classification of High Frequency Oscillations in intracranial EEG signals based on coupled time-frequency and image-related features

3. A Novel MEGNet for Classification of High-Frequency Oscillations in Magnetoencephalography of Epileptic Patients

4. FFT-Domain Signal Processing for Spectrally-Enhanced CP-OFDM Waveforms in 5G New Radio

5. An unsupervised fault diagnosis method for rolling bearing using STFT and generative neural networks

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