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Stress and Affect Detection on Resource-Constrained Devices

This repository contains code for the paper "Stress and Affect Detection on Resource-Constrained Devices", presented at the 18th International Conference on Machine Learning and Applications (2019), Boca Raton, FL, USA.

We discuss an efficient and accurate solution to stress detection in our paper. The datasets used are:

  • WESAD
  • SWELL-KW
  • DREAMER

Paper published in Proceedings of the 18th International Conference on Machine Learning and Applications (2019), IEEE Xplore.

Link: https://ieeexplore.ieee.org/document/8999216

Citation:

@inproceedings{8999216,
  author={A. {Ragav} and N. H. {Krishna} and N. {Narayanan} and K. {Thelly} and V. {Vijayaraghavan}},
  booktitle={2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA)},
  title={Scalable Deep Learning for Stress and Affect Detection on Resource-Constrained Devices},
  year={2019},
  volume={},
  number={},
  pages={1585-1592},
}

Authors: Abhijith Ragav, Nanda H Krishna, Naveen Narayanan, Kevin Thelly, Vineeth Vijayaraghavan

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