ParViT: A modified Vision Transformer architecture for Parkinson’s Disease identification using EEG signals-Reference-Cited by-同舟云学术

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ParViT: A modified Vision Transformer architecture for Parkinson’s Disease identification using EEG signals

Published:2024-05-03 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 International Conference on Smart Systems for applications in Electrical Sciences (ICSSES)
language:
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Author:

De Sagnik¹,Sayyad Amaan²,Kotian Hani³,Gupta Anil Kumar⁴

Affiliation:

1. Institute of Radio Physics and Electronics University of Calcutta,Kolkata,India

2. MESWCOE,Department of Computer Engineering,Pune,Maharashtra,India

3. DBIT,Department of Computer Engineering,Mumbai,India

4. HPC I&E Group Centre for Development of Advanced Computing,Pune,Maharashtra,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10560480/10561248/10561266.pdf?arnumber=10561266

Reference22 articles.

1. Detection of Parkinson’s disease using automated tunable Q wavelet transform technique with EEG signals

2. A deep learning approach for Parkinson’s disease diagnosis from EEG signals

3. A convolutional-recurrent neural network approach to resting-state EEG classification in Parkinson’s disease

4. Linear predictive coding distinguishes spectral EEG features of Parkinson's disease

5. Dynamical system based compact deep hybrid network for classification of Parkinson disease related EEG signals

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