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Drift Compensation on Massive Online Electronic-Nose Responses

Gas sensor drift is an important issue of electronic nose (E-nose) systems. This study follows this concern under the condition that requires an instant drift compensation with massive online E-nose responses. Recently, an active learning paradigm has been introduced to such condition. However, it d...

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Principais autores: Jianhua Cao, Tao Liu, Jianjun Chen, Tao Yang, Xiuxiu Zhu, Hongjin Wang
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2021-04-01
Serier:Chemosensors
Fag:
electronic nose
drift compensation
active learning
noisy label problem
mixed Gaussian model
expected entropy
Online adgang:https://www.mdpi.com/2227-9040/9/4/78
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