A semi-supervised learning framework for gas chimney detection based on sparse autoencoder and TSVM

Supervised classifiers play important roles in seismic interpretation. Especially in gas chimney detection, the multilayer perceptron (MLP), a supervised classifier, is widely used. However, the lack of labeled data usually limits applications of the supervised classifiers. To get more accurate seis...

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Bibliographic Details

Published in:	Journal of geophysics and engineering Vol. 16; no. 1; pp. 52 - 61
Main Authors:	Xu, Pengcheng, Lu, Wenkai, Wang, Benfeng
Format:	Journal Article
Language:	English
Published:	London Oxford University Press 01.02.2019
Subjects:	Accuracy Algorithms Classification Engineering Geophysics Lithology Neural networks Support vector machines transductive support vector machine gas chimney detection multi-attribute classification semi-supervised learning sparse autoencoder
ISSN:	1742-2132, 1742-2140
Online Access:	Get full text
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