@inproceedings{b7145c82e26e4d13b942666739ec4454,
title = "Spiking networks for improved cognitive abilities of edge computing devices",
abstract = "This concept paper highlights a recently opened opportunity for large scale analytical algorithms to be trained directly on edge devices. Such approach is a response to the arising need of processing data generated by natural person (a human being), also known as personal data. Spiking Neural networks are the core method behind it: suitable for a low latency energy-constrained hardware, enabling local training or re-training, while not taking advantage of scalability available in the Cloud.",
keywords = "Edge computing, Interactive computation, Spiking neural networks",
author = "Anton Akusok and Yoan Miche and Bj{\"o}rk, \{Kaj Mikael\} and Renjie Hu and Leal, \{Leonardo Espinosa\} and Amaury Lendasse",
note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2019 ; Conference date: 05-06-2019 Through 07-06-2019",
year = "2019",
month = jun,
day = "5",
doi = "10.1145/3316782.3321546",
language = "English (US)",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "307--308",
booktitle = "Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2019",
address = "United States",
}