LiteHAR: Lightweight Human Activity Recognition from WiFi Signals with Random Convolution Kernels
Implementation of the LiteHAR model by Hojjat Salehinejad and Shahrokh Valaee.
The corresponding paper has been accepted for presentation at IEEE ICASSP 2022. Paper on ArXiv: https://arxiv.org/abs/2201.09310
Here the link to the dataset used in the paper: https://github.com/ermongroup/Wifi_Activity_Recognition
Python >= 3.6 numpy pandas scikit-learn numba joblib
Run the bash script provided as: ./runner.sh
Setup parameters in the runner.sh:
python3.6 main.py -m rigRocket -k 10000 -cv 1 -e 20 -i ../Dataset/Data/
where
- i: path to the data
- e: number of epochs (if necessary)
- m: model
- k: number of kernels
- cv: number of cross-validation