63 citations · 90 across the 4 of their papers we have counts for
5 papers
Towards a Governance Framework for Brain Data
Marcello Ienca, Joseph J. Fins, Ralf J. Jox +17
The increasing availability of brain data within and outside the biomedical field, combined with the application of artificial intelligence (AI) to brain data analysis, poses a cha…
EEG-Based Brain-Computer Interfaces Are Vulnerable to Backdoor Attacks
Lubin Meng, Jian Huang, Zhigang Zeng +6
Research and development of electroencephalogram (EEG) based brain-computer interfaces (BCIs) have advanced rapidly, partly due to deeper understanding of the brain and wide adopti…
Tiny noise, big mistakes: Adversarial perturbations induce errors in Brain-Computer Interface spellers
Xiao Zhang, Dongrui Wu, Lieyun Ding +4
An electroencephalogram (EEG) based brain-computer interface (BCI) speller allows a user to input text to a computer by thought. It is particularly useful to severely disabled indi…
Applying Transfer Learning To Deep Learned Models For EEG Analysis
Axel Uran, Coert van Gemeren, Rosanne van Diepen +2
The introduction of deep learning and transfer learning techniques in fields such as computer vision allowed a leap forward in the accuracy of image classification tasks. Currently…
Context-aware learning for generative models
Serafeim Perdikis, Robert Leeb, Ricardo Chavarriaga +1
This work studies the class of algorithms for learning with side-information that emerge by extending generative models with embedded context-related variables. Using finite mixtur…