40 citations · 58 across the 4 of their papers we have counts for
4 papers
Deep learning for ECoG brain-computer interface: end-to-end vs. hand-crafted features
Maciej Śliwowski, Matthieu Martin, Antoine Souloumiac +2
In brain signal processing, deep learning (DL) models have become commonly used. However, the performance gain from using end-to-end DL models compared to conventional ML approache…
Impact of dataset size and long-term ECoG-based BCI usage on deep learning decoders performance
Maciej Śliwowski, Matthieu Martin, Antoine Souloumiac +2
In brain-computer interfaces (BCI) research, recording data is time-consuming and expensive, which limits access to big datasets. This may influence the BCI system performance as m…
Decoding ECoG signal into 3D hand translation using deep learning
Maciej Śliwowski, Matthieu Martin, Antoine Souloumiac +2
Motor brain-computer interfaces (BCIs) are a promising technology that may enable motor-impaired people to interact with their environment. Designing real-time and accurate BCI is…
Automatic Segmentation and Location Learning of Neonatal Cerebral Ventricles in 3D Ultrasound Data Combining CNN and CPPN
Matthieu Martin, Bruno Sciolla, Michaël Sdika +2
Preterm neonates are highly likely to suffer from ventriculomegaly, a dilation of the Cerebral Ventricular System (CVS). This condition can develop into life-threatening hydrocepha…