An efficient Parkinson's disease detection framework: Leveraging time-frequency representation and AlexNet convolutional neural network
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Siuly, Siuly 
ORCID: 0000-0003-2491-0546, Khare, Smith K ORCID: 0000-0001-8365-1092, Kabir, Enamul, Sadiq, Muhammad Tariq ORCID: 0000-0002-7410-5951 and Wang, Hua ORCID: 0000-0002-8465-0996
(2024)
An efficient Parkinson's disease detection framework: Leveraging time-frequency representation and AlexNet convolutional neural network.
Computers in Biology and Medicine, 174.
ISSN 0010-4825
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| Item type | Article |
| URI | https://vuir.vu.edu.au/id/eprint/48602 |
| DOI | 10.1016/j.compbiomed.2024.108462 |
| Official URL | https://www.sciencedirect.com/science/article/pii/... |
| Subjects | Current > FOR (2020) Classification > 3102 Bioinformatics and computational biology Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
| Keywords | Parkinson’s disease detection; electroencephalogram signals; time-frequency representation; wavelet scattering transform; AlexNet CNN; feature extraction |
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