A CNN-Based E-Nose Using Time Series Features for Food Freshness Classification-Reference-Cited by-同舟云学术

A CNN-Based E-Nose Using Time Series Features for Food Freshness Classification

Published:2023-03-15 Issue:6 Volume:23 Page:6027-6038
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Ren Xudong¹^ORCID,Wang Yudong¹,Huang Yuan¹^ORCID,Mustafa Muhammad¹^ORCID,Sun Dongbo¹^ORCID,Xue Feng²^ORCID,Chen Dongliang¹,Xu Lei³^ORCID,Wu Feng¹

Affiliation:

1. School of Microelectronics, University of Science and Technology of China, Hefei, China

2. School of Information Science and Technology, University of Science and Technology of China, Hefei, China

3. Hefei National Research Center for Physical Sciences at the Microscale and the School of Microelectronics, University of Science and Technology of China, Hefei, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10068826/10043773.pdf?arnumber=10043773

Reference48 articles.

1. Odor Recognition in Multiple E-Nose Systems With Cross-Domain Discriminative Subspace Learning

2. Development of an auto-calibrated interfacing circuit for thick film multi-gas sensor

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4. Low-voltage low-power integrated analog lock-in amplifier for gas sensor applications

5. Domain Adaptation Extreme Learning Machines for Drift Compensation in E-Nose Systems

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