Multi-Classifier Tree With Transient Features for Drift Compensation in Electronic Nose

Multi-Classifier Tree With Transient Features for Drift Compensation in Electronic Nose

<p dir="ltr">Long term sensors drift is a challenging problem to solve for instruments like an Electronic Nose System (ENS). These electronic instruments rely on Machine Learning (ML) algorithms for recognizing the sensed odors. The effect of long-term drift influences the performanc...

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Bibliographic Details
Main Author: Atiq Ur Rehman (8843024) (author)
Other Authors: Samir Brahim Belhaouari (9427347) (author), Muhammad Ijaz (677144) (author), Amine Bermak (1895947) (author), Mounir Hamdi (14150652) (author)
Published: 2020
Subjects:
Engineering
Electronics, sensors and digital hardware
Information and computing sciences
Machine learning
Sensors
Transient analysis
Sensor systems
Sensor phenomena and characterization
Gas detectors
Steady-state
Time factors
Artificial olfaction
Electronic nose
Heuristic optimization
Industrial gases
Sensors drift
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