PAT is a unified training framework that jointly improves accuracy, robustness, and privacy in EEG decoding for BCIs under centralized source-free, federated source-free, and privacy-preserved source data transfer scenarios.
Alignment-based adversari al training (ABA T) for improving the robustness and accuracy of EEG-based BCIs,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.HC 1years
2024 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
PAT: Privacy-Preserving Adversarial Transfer for Accurate, Robust and Privacy-Preserving EEG Decoding
PAT is a unified training framework that jointly improves accuracy, robustness, and privacy in EEG decoding for BCIs under centralized source-free, federated source-free, and privacy-preserved source data transfer scenarios.