Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Arl Eegmodels | 622 | 2 years ago | 6 | other | Python | |||||
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow | ||||||||||
Eeg Dl | 563 | 2 years ago | 10 | May 13, 2020 | 4 | mit | Python | |||
A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow. | ||||||||||
Eeg Motor Imagery Classification Cnns Tensorflow | 118 | 2 years ago | Python | |||||||
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow | ||||||||||
Sleepeegnet | 106 | 3 years ago | 13 | Python | ||||||
SleepEEGNet: Automated Sleep Stage Scoring with Sequence to Sequence Deep Learning Approach | ||||||||||
Autosleepscorer | 86 | 2 years ago | 14 | agpl-3.0 | Python | |||||
An open-source sleep stage classification Python package | ||||||||||
Tinysleepnet | 76 | a year ago | 3 | apache-2.0 | Python | |||||
TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG by Akara Supratak and Yike Guo from The Faculty of ICT, Mahidol University and Imperial College London respectively | ||||||||||
Eeg_classification | 37 | 4 years ago | apache-2.0 | Python | ||||||
EEG Sleep stage classification using CNN with Keras | ||||||||||
Mneflow | 31 | a year ago | 4 | May 19, 2022 | bsd-3-clause | Python | ||||
Neural networks for EEG-MEG decoding with MNE-python and Tensorflow. | ||||||||||
Motor Imagery Tasks Classification Using Eeg Data | 29 | 6 years ago | 1 | Jupyter Notebook | ||||||
Implementation of Deep Neural Networks in Keras and Tensorflow to classify motor imagery tasks using EEG data | ||||||||||
Sleep_staging_shhs | 24 | 7 years ago | 3 | Python | ||||||
Code for the paper "A Convolutional neural network for sleep stage scoring from raw single-channel EEG" |