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ambitious-octopus / MI-EEG-1D-CNN

A new approach based on a 10-layer one-dimensional convolution neural network (1D-CNN) to classify five brain states (four MI classes plus a 'baseline' class) using a data augmentation algorithm and a limited number of EEG channels. Paper: https://doi.org/10.1088/1741-2552/ac4430
GNU General Public License v3.0
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LSTM single-subject approach #17

Closed ambitious-octopus closed 2 years ago

ambitious-octopus commented 2 years ago

Code

  1. Generate data and understand how tf.data works
  2. How to split train and test!
  3. Clean the repo.

Theory:

  1. Understand how the hell a LSTM works.
ambitious-octopus commented 2 years ago

@Kubasinska i will clean the repo!

ambitious-octopus commented 2 years ago

Resource: https://colah.github.io/posts/2015-08-Understanding-LSTMs/