Lightweight and High-Precision Gas Identification Neural Network for Embedded Electronic Nose Devices-Reference-Cited by-同舟云学术

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Lightweight and High-Precision Gas Identification Neural Network for Embedded Electronic Nose Devices

Published:2024-04-15 Issue:8 Volume:24 Page:13666-13675
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Hu Anyu¹^ORCID,Zhai Shoupei¹,Cui Baile¹,Zhao Zheng¹,Jin Jing¹,Zhang Chao²,Wang Wen³^ORCID,Pan Yong⁴

Affiliation:

1. State Key Laboratory of Acoustics, Chinese Academy of Sciences, Beijing, China

2. Beijing Institute of Control and Electronic Technology, Beijing, China

3. State Key Laboratory of Acoustics Institute of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing, China

4. State Key Laboratory of NBC Protection for Civilian, Beijing, China

Funder

National Key Research and Development Program

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10500449/10466508.pdf?arnumber=10466508

Reference32 articles.

1. A Review on Electronic Nose: Coherent Taxonomy, Classification, Motivations, Challenges, Recommendations and Datasets

2. Different Ways to Apply a Measurement Instrument of E-Nose Type to Evaluate Ambient Air Quality with Respect to Odour Nuisance in a Vicinity of Municipal Processing Plants

3. Development of an electronic-nose system for fruit maturity and quality monitoring

4. Application of electronic nose for industrial odors and gaseous emissions measurement and monitoring – An overview

5. Application of Electronic-Nose Technologies and VOC-Biomarkers for the Noninvasive Early Diagnosis of Gastrointestinal Diseases

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