Online Scent Classification by Ion-Mobility Spectrometry Sequences-Reference-Cited by-同舟云学术

Online Scent Classification by Ion-Mobility Spectrometry Sequences

Published:2019-07-30 Issue: Volume:5 Page:
ISSN:2297-4687
Container-title:Frontiers in Applied Mathematics and Statistics
language:
Short-container-title:Front. Appl. Math. Stat.

Author:

Müller Philipp,Salminen Katri,Kontunen Anton,Karjalainen Markus,Isokoski Poika,Rantala Jussi,Leivo Joni,Väliaho Jari,Kallio Pasi,Lekkala Jukka,Surakka Veikko

Funder

Academy of Finland

Suomen Kulttuurirahasto

Publisher

Frontiers Media SA

Subject

Applied Mathematics,Statistics and Probability

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1. Recent advances in technologies toward the development of 2D materials-based electronic noses;TrAC Trends in Analytical Chemistry;2023-09

2. A comparison of online methods for change point detection in ion-mobility spectrometry data;Array;2022-07

3. People Stink!: Towards Identification of People from Breath Samples;2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN);2022-05-29

4. A Comparison of Various Algorithms for Classification of Food Scents Measured with an Ion Mobility Spectrometry;Sensors;2021-01-07

5. Transferring scents over a communication network;Proceedings of the 23rd International Conference on Academic Mindtrek;2020-01-29