MISC

査読有り
2018年

Odor classification for human breath using neural networks

Advances in Intelligent Systems and Computing
  • Sigeru Omatu

620
開始ページ
293
終了ページ
300
記述言語
英語
掲載種別
DOI
10.1007/978-3-319-62410-5_36
出版者・発行元
Springer Verlag

The principle of metal-oxide gas sensors is based on oxidation and reduction rule. The aim of this paper is to classify odors of breath in which several gasses are mixed. Using neural networks to train a specific odor we classify mixed odors. First, we train a layered neural network for specific odor which is main component of our breath. Then we apply the breath data to classify the other components.

リンク情報
DOI
https://doi.org/10.1007/978-3-319-62410-5_36
DBLP
https://dblp.uni-trier.de/rec/conf/dcai/Omatu17
URL
http://dblp.uni-trier.de/db/conf/dcai/dcai2017.html#conf/dcai/Omatu17
ID情報
  • DOI : 10.1007/978-3-319-62410-5_36
  • ISSN : 2194-5357
  • DBLP ID : conf/dcai/Omatu17
  • SCOPUS ID : 85022191872

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