Shallow Convolutional Neural Networks for Human Activity Recognition using Wearable Sensors

[IEEE TIM 2021-1] Shallow Convolutional Neural Networks for Human Activity Recognition using Wearable Sensors

All of datasets we use in this paper can be download from Internet and you can find we how to process data in this paper.
This is my first time to open source, so there maybe some problems in my codes and I will improve this project in the near feature.
Thanks!

Requirements

● Python3
● PyTorch (My version 1.9.0+cu111, please choose compatibility with your computer)
● Scikit-learn
● Numpy

How to train

UCI-HAR dataset

Get UCI dataset from UCI Machine Learning Repository(http://archive.ics.uci.edu/ml/index.php), do data pre-processing by sliding window strategy and split the data into training and test sets