Encoded Image-Based Time Series Classification for Improving Colorimetric Detection of Hydrogen Sulfide (H2S)
Author:
Affiliation:
1. Advanced Mechatronics R&D Group, Korea Institute of Industrial Technology,Daegu,Republic of Korea
2. Kyungpook National University,Department of Mechanical Engineering,Daegu,Republic of Korea
Funder
Korea Institute of Industrial Technology
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9966996/9966997/09967351.pdf?arnumber=9967351
Reference19 articles.
1. Deep learning for time series classification: a review
2. A Fundamental Study on Estimating the Concentration of Carbon Monoxide (CO) By Fabric-Based Colorimetric Analysis Using an Optical RGB Color Sensor;chang-hyun;ECS Meeting Abstracts,2020
3. Multi-Dimensional Encoding Image Based Time Series Feature Extraction for Improved Colorimetric Gas Concentration Estimation;chang-hyun;ECS Meeting Abstracts,2021
4. Multi-scale signed recurrence plot based time series classification using inception architectural networks
5. Polyester (PET) Fabric dyed with Lead (II) acetate-based Colorimetric Sensor for Detecting Hydrogen Sulfide (H2S)
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