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Greatest papers with code

Decoding P300 Variability using Convolutional Neural Networks

Frontiers in Human Neuroscience 2019 vlawhern/arl-eegmodels

Deep convolutional neural networks (CNN) have previously been shown to be useful tools for signal decoding and analysis in a variety of complex domains, such as image processing and speech recognition.

EEG EEG DECODING SPEECH RECOGNITION

Deep learning with convolutional neural networks for EEG decoding and visualization

15 Mar 2017gibranfp/P300-CNNT

PLEASE READ AND CITE THE REVISED VERSION at Human Brain Mapping: http://onlinelibrary. wiley. com/doi/10. 1002/hbm. 23730/full Code available here: https://github. com/robintibor/braindecode

EEG EEG DECODING

Subject-Aware Contrastive Learning for Biosignals

30 Jun 2020zacharycbrown/ssl_baselines_for_biosignal_feature_extraction

Datasets for biosignals, such as electroencephalogram (EEG) and electrocardiogram (ECG), often have noisy labels and have limited number of subjects (<100).

ANOMALY DETECTION DATA AUGMENTATION EEG EEG DECODING SELF-SUPERVISED LEARNING TIME SERIES

Decoding kinetic features of hand motor preparation from single‐trial EEG using convolutional neural networks

11 Aug 2020ragatti/STSnet

These results show that movement speed and force can be accurately predicted from single‐trial EEG, and that the prediction strategies may provide useful neurophysiological information about motor preparation.

CLASSIFICATION EEG EEG DECODING TIME SERIES TIME SERIES CLASSIFICATION