Recognition of Ethylene Plasma Spectra 1D Data Based on Deep Convolutional Neural Networks

Recognition of Ethylene Plasma Spectra 1D Data Based on Deep Convolutional Neural Networks

As a commonly used plasma diagnostic method, the spectral analysis methodology generates a large amount of data and has a complex quantitative relationship with discharge parameters, which result in low accuracy and time-consuming operation of traditional manual spectral recognition methods. To quic...

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Bibliographic Details
Main Authors: Baoxia Li, Wenzhuo Chen, Shaohuang Bian, Lusi A, Xiaojiang Tang, Yang Liu, Junwei Guo, Dan Zhang, Cheng Yang, Feng Huang
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Electronics
Subjects:
ethylene plasma
spectral recognition
deep convolutional neural network
Online Access:https://www.mdpi.com/2079-9292/13/5/983

Internet

https://www.mdpi.com/2079-9292/13/5/983

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