Feature Extraction and Classification of Cataluminescence Images Based on Sparse Coding Convolutional Neural Networks

The atmosphere of human existence is increasingly complex, and various harmful gases seriously endanger human health. Therefore, it is necessary to quickly and accurately detect trace toxic gases. With the application progress of cataluminescence (CTL) in the detection of harmful gases, this article...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on instrumentation and measurement Jg. 70; S. 1 - 11
Hauptverfasser:	Shi, Guolong, He, Yigang, Zhang, Chaolong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Artificial neural networks Back propagation Back propagation networks Cataluminescence (CTL) sensor Classification Coding Convolution deep learning Eigenvectors Feature extraction Gases Image classification Internet of Things Kernel Luminescence Neural networks Sensor arrays sparse coding convolutional neural networks (SCNNs) Temperature sensors Visual fields
ISSN:	0018-9456, 1557-9662
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!