Automated design of a convolutional neural network with multi-scale filters for cost-efficient seismic data classification

The authors present an automated design approach to propose a new neural network architecture for seismic data analysis. The new architecture classifies multiple seismic reflection datasets at extremely low computational cost compared with conventional architectures for image classification.

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Detalles Bibliográficos
Autores principales:	Zhi Geng, Yanfei Wang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/47df02517dab422f98ad99c5a7c03762
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spelling	oai:doaj.org-article:47df02517dab422f98ad99c5a7c037622021-12-02T18:18:47ZAutomated design of a convolutional neural network with multi-scale filters for cost-efficient seismic data classification10.1038/s41467-020-17123-62041-1723https://doaj.org/article/47df02517dab422f98ad99c5a7c037622020-07-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-17123-6https://doaj.org/toc/2041-1723The authors present an automated design approach to propose a new neural network architecture for seismic data analysis. The new architecture classifies multiple seismic reflection datasets at extremely low computational cost compared with conventional architectures for image classification.Zhi GengYanfei WangNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-11 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Zhi Geng Yanfei Wang Automated design of a convolutional neural network with multi-scale filters for cost-efficient seismic data classification
description	The authors present an automated design approach to propose a new neural network architecture for seismic data analysis. The new architecture classifies multiple seismic reflection datasets at extremely low computational cost compared with conventional architectures for image classification.
format	article
author	Zhi Geng Yanfei Wang
author_facet	Zhi Geng Yanfei Wang
author_sort	Zhi Geng
title	Automated design of a convolutional neural network with multi-scale filters for cost-efficient seismic data classification
title_short	Automated design of a convolutional neural network with multi-scale filters for cost-efficient seismic data classification
title_full	Automated design of a convolutional neural network with multi-scale filters for cost-efficient seismic data classification
title_fullStr	Automated design of a convolutional neural network with multi-scale filters for cost-efficient seismic data classification
title_full_unstemmed	Automated design of a convolutional neural network with multi-scale filters for cost-efficient seismic data classification
title_sort	automated design of a convolutional neural network with multi-scale filters for cost-efficient seismic data classification
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/47df02517dab422f98ad99c5a7c03762
work_keys_str_mv	AT zhigeng automateddesignofaconvolutionalneuralnetworkwithmultiscalefiltersforcostefficientseismicdataclassification AT yanfeiwang automateddesignofaconvolutionalneuralnetworkwithmultiscalefiltersforcostefficientseismicdataclassification
_version_	1718378211158523904

Automated design of a convolutional neural network with multi-scale filters for cost-efficient seismic data classification

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