Widespread bathymetric outliers detection and elimination based on conditional variational autoencoder generative adversarial network

Widespread bathymetric outliers detection and elimination based on conditional variational autoencoder generative adversarial network

In view of the complexity and variability of bathymetric data missing and exception, an algorithm named CVAE-GAN to detect and eliminate the widespread bathymetric outliersis proposed. Firstly, the proposed model is an alternative to traditional generative adversarial network (GAN) training methods,...

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Bibliographic Details
Main Authors: ZHANG Ruichen, BIAN Shaofeng, LIU Yanchun, LI Houpu
Format: Article
Language:zho
Published: Surveying and Mapping Press 2019-09-01
Series:Acta Geodaetica et Cartographica Sinica
Subjects:
bathymetricoutliers
data processing
conditional variational autoencoder
generative adversarial network
feature extraction
Online Access:http://html.rhhz.net/CHXB/html/2019-9-1182.htm

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http://html.rhhz.net/CHXB/html/2019-9-1182.htm

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