M2FL-CCC: Multibranch Multilayer Feature Leaning and Comprehensive Classification Criterion for Gas Sensor Drift Compensation
Author:
Affiliation:
1. College of Artificial Intelligence, Southwest University, Beibei, China
2. Brain-Inspired Computing and Intelligent Control of Chongqing Key Laboratory, Beibei, China
Funder
National Natural Science Foundation of China
National Training Program of Innovation and Entrepreneurship for Undergraduates
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/19/10012124/10187901.pdf?arnumber=10187901
Reference38 articles.
1. An Attention-Based Deep Sequential GRU Model for Sensor Drift Compensation
2. An optimized deep convolutional neural network for dendrobium classification based on electronic nose
3. A Drift-Compensating Novel Deep Belief Classification Network to Improve Gas Recognition of Electronic Noses
4. Deep learning models for classification of gases detected by sensor arrays of artificial nose
5. Gas identification with drift counteraction for electronic noses using augmented convolutional neural network
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