This is the official repository for the research paper
Looking deep into ShallowConvNet: Towards Explainable AI in EEG Dementia Classification
Submitted to [TO DO].
In this work, [TO DO]
Scripts used to generate the results presented in the paper are available in this repository. In AllFnc folder, the Python file eegvislib.py was developed with the intent to be used as library for insepcting kernels and feature maps in DL applications, with a focus in EEG data. The Jupyter Notebook ModelVisualization.ipynb shows a proof of concept of the usefulness. In details, the library can help researchers to inspect both the weights and the feature maps, learned by the neural network.
If you find codes and results useful for your research, please concider citing our work. It would help us to continue our research. At the moment, we are working on a research paper to submit to [TO DO]
Contributors:
- M.Sc. Andrea Zanola
- M.Sc. Louis Fabrice Tshimanga
- Eng. Federico Del Pup
- Prof. Manfredo Atzori
The code is released under the MIT License