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Transfer learning and SpecAugment applied to SSVEP based BCI classification

  • Published:2021-05 Issue: Volume:67 Page:102542
  • ISSN:1746-8094
  • Container-title:Biomedical Signal Processing and Control
  • language:en
  • Short-container-title:Biomedical Signal Processing and Control

Author:

Bassi Pedro R.A.S.,Rampazzo Willian,Attux Romis

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing

Reference23 articles.

1. ImageNet: A Large-Scale Hierarchical Image Database;Deng;In: CVPR09,2009

2. Deep Learning, vol. 1;Goodfellow,2016

3. A benchmark dataset for ssvep-based brain-computer interfaces;Wang;IEEE Trans. Neural Syst. Rehabil. Eng.,2017

4. CNN architectures for large-scale audio classification.;Hershey;International Conference on Acoustics, Speech and Signal Processing (ICASSP),2017

5. K. Simonyan, A. Zisserman, Very deep convolutional networks for large-scale image recognition. 2014. arXiv:1409.1556.

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1. Enhancing cross-subject transfer performance for SSVEP identification using small data-based transferability evaluation;Biomedical Signal Processing and Control;2024-08

2. A comprehensive review of deep learning power in steady-state visual evoked potentials;Neural Computing and Applications;2024-07-23

3. Impact of Fragmentation on Temporal Event Localization for Speech EEG;2024 International Conference on Signal Processing and Communications (SPCOM);2024-07-01

4. Deep transfer learning-based SSVEP frequency domain decoding method;Biomedical Signal Processing and Control;2024-03

5. A Novel Data Augmentation Approach Using Mask Encoding for Deep Learning-Based Asynchronous SSVEP-BCI;IEEE Transactions on Neural Systems and Rehabilitation Engineering;2024
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