Using deep data augmentation training to address software and hardware heterogeneities in wearable and smartphone sensing devices

Akhil Mathur, Tianlin Zhang, Sourav Bhattacharya, Petar Velickovic, Leonid Joffe, Nicholas D. Lane, Fahim Kawsar, Pietro Liò. Using deep data augmentation training to address software and hardware heterogeneities in wearable and smartphone sensing devices. In Luca Mottola, Jie Gao, Pei Zhang, editors, Proceedings of the 17th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2018, Porto, Portugal, April 11-13, 2018. pages 200-211, IEEE / ACM, 2018. [doi]

@inproceedings{MathurZBVJLKL18,
  title = {Using deep data augmentation training to address software and hardware heterogeneities in wearable and smartphone sensing devices},
  author = {Akhil Mathur and Tianlin Zhang and Sourav Bhattacharya and Petar Velickovic and Leonid Joffe and Nicholas D. Lane and Fahim Kawsar and Pietro Liò},
  year = {2018},
  url = {http://dl.acm.org/citation.cfm?id=3207994},
  researchr = {https://researchr.org/publication/MathurZBVJLKL18},
  cites = {0},
  citedby = {0},
  pages = {200-211},
  booktitle = {Proceedings of the 17th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2018, Porto, Portugal, April 11-13, 2018},
  editor = {Luca Mottola and Jie Gao and Pei Zhang},
  publisher = {IEEE / ACM},
}