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Greatest papers with code

SGDR: Stochastic Gradient Descent with Warm Restarts

13 Aug 2016rwightman/pytorch-image-models

Partial warm restarts are also gaining popularity in gradient-based optimization to improve the rate of convergence in accelerated gradient schemes to deal with ill-conditioned functions.

EEG STOCHASTIC OPTIMIZATION

Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks

19 Nov 2015pbashivan/EEGLearn

One of the challenges in modeling cognitive events from electroencephalogram (EEG) data is finding representations that are invariant to inter- and intra-subject differences, as well as to inherent noise associated with such data.

CLASSIFICATION EEG TIME SERIES VIDEO CLASSIFICATION

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

Compact Convolutional Neural Networks for Classification of Asynchronous Steady-state Visual Evoked Potentials

12 Mar 2018vlawhern/arl-eegmodels

Steady-State Visual Evoked Potentials (SSVEPs) are neural oscillations from the parietal and occipital regions of the brain that are evoked from flickering visual stimuli.

CLASSIFICATION EEG

EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces

23 Nov 2016vlawhern/arl-eegmodels

We introduce the use of depthwise and separable convolutions to construct an EEG-specific model which encapsulates well-known EEG feature extraction concepts for BCI.

EEG

DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

12 Mar 2017akaraspt/deepsleepnet

This demonstrated that, without changing the model architecture and the training algorithm, our model could automatically learn features for sleep stage scoring from different raw single-channel EEGs from different datasets without utilizing any hand-engineered features.

EEG SLEEP STAGE DETECTION

Attention-based Graph ResNet for Motor Intent Detection from Raw EEG signals

25 Jun 2020SuperBruceJia/EEG-DL

In previous studies, decoding electroencephalography (EEG) signals has not considered the topological relationship of EEG electrodes.

EEG INTENT DETECTION SEIZURE PREDICTION

GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-resolved EEG Motor Imagery Signals

16 Jun 2020SuperBruceJia/EEG-DL

To conclude, the GCNs-Net filters EEG signals based on the functional topological relationship, which manages to decode relevant features for brain motor imagery.

EEG

Deep Feature Mining via Attention-based BiLSTM-GCN for Human Motor Imagery Recognition

2 May 2020SuperBruceJia/EEG-DL

The introduced deep feature mining approach can precisely recognize human motion intents from raw EEG signals, which paves the road to translate the EEG based MI recognition to practical BCI systems.

EEG