Can Ensemble Deep Learning Identify People by Their Gait Using Data Collected from Multi-Modal Sensors in Their Insole?
This repository is the official implementation of "Can Ensemble Deep Learning Identify People by Their Gait Using Data Collected from Multi-Modal Sensors in Their Insole?"
To install requirements:
pip install -r requirements.txt
The averaging ensemble model utilizes a CNN and a RNN model trained independently. The trained models are saved in folders especified in the source code. The required sequence to train the tri-modal is as follows:
cd code/tri-modal
python Experiments_CNN.py
python Experiments_RNN.py
python Experiments_Ensemble.py
We repeat the experiment 20 times for each K and for three types of Monte Carlo Cross-Validation (MCCV) methods, which are MCCV (30%), Sub-MCCV, (50%), and MCCV (50%) described in the paper. For each repetition, our proposed method is trained and tested independently, then the averaged evaluation metrics are summarized.
Tri-modal performance:
t-SNE:
Nelson Minaya [email protected]
Nhat Le [email protected]