MEGDNN

Deep Learning for Activity Recognition based on Magnetoencephalography (MEG) Data

This project consists of: run_experiment.py utils.py models.py

config_conv.yaml config_linear.yaml

To start with the code you should first look at the run experiment file.

Authors: Amber Koelfat Efraim Dahl Zihan Zou Timofey Senchenko Marijn Prins Boris Vasilyev

Name		Name	Last commit message	Last commit date
Latest commit History 24 Commits
.gitignore		.gitignore
Accuracy_DeepLearning.R		Accuracy_DeepLearning.R
LSTM_testAcc_20_samples.txt		LSTM_testAcc_20_samples.txt
MEG-CNN-2D-20samp-accuracies.csv		MEG-CNN-2D-20samp-accuracies.csv
MEG_project.ipynb		MEG_project.ipynb
README.md		README.md
baseline_svm.ipynb		baseline_svm.ipynb
config_conv.yaml		config_conv.yaml
config_linear.yaml		config_linear.yaml
config_lstm.yaml		config_lstm.yaml
denoising.ipynb		denoising.ipynb
mega_nalysis.ipynb		mega_nalysis.ipynb
mixed_sample_accuracies.csv		mixed_sample_accuracies.csv
models.py		models.py
run_experiment.py		run_experiment.py
utils.py		utils.py

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