Mixture Gases Classification Based on Multi-Label One-Dimensional Deep Convolutional Neural Network

Mixture Gases Classification Based on Multi-Label One-Dimensional Deep Convolutional Neural Network

In this paper, we present a novel one-dimensional deep convolutional neural network (1D-DCNN) with a multi-label-way-based algorithm for comprehensively and automatically extracting features and classifying mixture gases. Although a number of pattern recognition methods have been used to analyze the...

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Bibliographic Details
Main Authors: Xiaojin Zhao, Zhihuang Wen, Xiaofang Pan, Wenbin Ye, Amine Bermak
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Mixture gases recognition
deep convolutional neural network
multi-label classification
Online Access:https://ieeexplore.ieee.org/document/8611207/

Internet

https://ieeexplore.ieee.org/document/8611207/

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