Enhancing E-Nose Performance via Metal-Oxide Based MEMS Sensor Arrays Optimization and Feature Alignment for Drug Classification

Enhancing E-Nose Performance via Metal-Oxide Based MEMS Sensor Arrays Optimization and Feature Alignment for Drug Classification

This article introduces a novel approach to improve electronic nose classification accuracy by optimizing sensor arrays and aligning features. This involves selecting the best sensor combinations and reducing redundant information for better odor recognition. We employ a feature alignment algorithm...

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Bibliographic Details
Main Authors: Ruiwen Kong, Wenfeng Shen, Yang Gao, Dawu Lv, Ling Ai, Weijie Song, Ruiqin Tan
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Sensors
Subjects:
electronic nose
MEMS
transfer learning
ReliefF algorithm
feature alignment
Online Access:https://www.mdpi.com/1424-8220/25/5/1480
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