Benchmarking learning networks on eat-sleep conditions

Victor Parque, Hammed Obasekore, Solomon Oladayo, Tomoyuki Miyashita

研究成果: Conference contribution

抜粋

Human activity recognition technologies are key to promote healthy life styles, and potential to offer explanations to study the origin of complex diseases. In particular, it is well-known that the quick transition between eating and sleeping is known to trigger unfavorable conditions for healthy life style. In this paper we describe our observations and insights in the benchmarking of the state of the art classification models based on graph representations to classify activities comprising drinking, eating, walking, running and sleeping.

元の言語English
ホスト出版物のタイトル2019 IEEE 1st Global Conference on Life Sciences and Technologies, LifeTech 2019
出版者Institute of Electrical and Electronics Engineers Inc.
ページ29-30
ページ数2
ISBN(電子版)9781728105437
DOI
出版物ステータスPublished - 2019 3
イベント1st IEEE Global Conference on Life Sciences and Technologies, LifeTech 2019 - Osaka, Japan
継続期間: 2019 3 122019 3 14

出版物シリーズ

名前2019 IEEE 1st Global Conference on Life Sciences and Technologies, LifeTech 2019

Conference

Conference1st IEEE Global Conference on Life Sciences and Technologies, LifeTech 2019
Japan
Osaka
期間19/3/1219/3/14

ASJC Scopus subject areas

  • Artificial Intelligence
  • Health Informatics
  • Neuroscience (miscellaneous)
  • Computer Science Applications
  • Biomedical Engineering

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  • これを引用

    Parque, V., Obasekore, H., Oladayo, S., & Miyashita, T. (2019). Benchmarking learning networks on eat-sleep conditions. : 2019 IEEE 1st Global Conference on Life Sciences and Technologies, LifeTech 2019 (pp. 29-30). [8883998] (2019 IEEE 1st Global Conference on Life Sciences and Technologies, LifeTech 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/LifeTech.2019.8883998