Mar 27, 2019 · We propose an adversarial inference approach to extend such deep learning models to learn session-invariant person-discriminative representations.

II. Prior Work · III. Adversarial Convolutional... · Discussion

This work proposes an adversarial inference approach to extend deep learning models to learn session-invariant person-discriminative representations that ...

Mar 30, 2019 · We propose an adversarial inference approach to extend such deep learning models to learn session-invariant person-discriminative representations.

Using adversarial learning within a deep convolutional network, we empirically assess and show improvements with our approach based on longitudinally collected ...

This paper, for the first time, explores multiple classical and state-of-the-art adversarial defense approaches in EEG-based BCIs.

We propose a further step towards invariance of EEG deep learning frameworks in a systemic way during model training. We introduce an adversarial inference ...

Oct 16, 2024 · This adversarial learning approach has demonstrated remarkable effectiveness in generating artifact-free EEG signals. This study takes an ...

Jun 1, 2022 · In this paper, we introduce a new training approach for deep learning to learn time-permanent and subject-unique embeddings towards an EEG biometric system.

We introduce this study to the recent proposed deep learning-based approaches in BCI using EEG data (from 2017 to 2022).