arl-eegmodels
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vlawhern
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
So, I decided to use Google Colab for my interface of choice for my project. I have opted to upgrade to Colab Pro to see if it will benefit me....
Hello, I am working on a course project using 4 channels of EEG signals and 256 as sampling rate for BCI application of binary image classification. My training dataset size...
Hello. I am trying to reproduce experimental results of BCI Competition IV dataset 2a for within classification in the paper. I reused EEGNet class but got mean accuracy 60~63. I...
I am wondering if it would be possible to estimate the amplitudes and latencies of ERP waveforms using EEGnet. If this is possible, could you please explain how I might...
 There is a problem with drawing the obfuscation matrix
Hi, I have got the DeepLIFT to work and understood the method, though the two other methods mentioned in [[1]](http://stacks.iop.org/1741-2552/15/i=5/a=056013) have I not managed to implement. For the first method,...
Hi: I tried to use the braindecode in cross-subject case and recreate the results from the paper, are there any examples I can learn from ?
- Building on issue #29 and checking the TF2 pull request repo on DeepExplain I made this notebook tutorial on explainability using DeepLift. It covers all operations from packages install...
I tried to reproduce your paper work, but I looked at your project and couldn't find a complete program entrance. Can you tell me how to run this project?
I cannot replicate the within-subject experimental results of BCI Competition IV dataset 2a using PyTorch Here is my code for data processing ```python def getdata_A_T_22(filename,ids): raw_gdf = mne.io.read_raw_gdf(filename, stim_channel="auto", verbose='ERROR',...
