Abstract: With the rapid development of deep learning in the field ... Despite significant progress in few-shot learning, current few-shot image classification methods have not fully exploited the ...

Methods: The model first used a variational autoencoder (VAE) network for unsupervised learning of EEG and EMG signals ... Despite the model’s excellent performance in deep feature extraction and ...

Feature extraction ... the model is susceptible to adversarial perturbations, with a considerable proportion of samples misclassified at low epsilon values. This project highlights the potential of ...

Table 1 Extraction ... feature dimensions, the potential improvement in classification results could be achieved by increasing the size of the data sample, implementing dimensionality reduction, or ...

The study was currently limited to the population size, a larger sample size with more patients is required to better train the deep-learning model ... By combining all these features, the deep ...