Data augmentation using conditional generative adversarial network (cGAN): Application for prediction of corrosion pit depth and testing using neural network

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Main Author: Xingye HUANG
Format: Article
Language:zho
Published: Editorial Office of Oil & Gas Storage and Transportation 2024-11-01
Series:You-qi chuyun
Online Access:https://yqcy.pipechina.com.cn/cn/article/doi/
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author Xingye HUANG
author_facet Xingye HUANG
author_sort Xingye HUANG
collection DOAJ
format Article
id doaj-art-80b468447fc241f3b8f6c69a4ce2a6dc
institution DOAJ
issn 1000-8241
language zho
publishDate 2024-11-01
publisher Editorial Office of Oil & Gas Storage and Transportation
record_format Article
series You-qi chuyun
spelling doaj-art-80b468447fc241f3b8f6c69a4ce2a6dc2025-08-20T02:57:04ZzhoEditorial Office of Oil & Gas Storage and TransportationYou-qi chuyun1000-82412024-11-01431113201320yqcy-43-11-1320Data augmentation using conditional generative adversarial network (cGAN): Application for prediction of corrosion pit depth and testing using neural networkXingye HUANGhttps://yqcy.pipechina.com.cn/cn/article/doi/
spellingShingle Xingye HUANG
Data augmentation using conditional generative adversarial network (cGAN): Application for prediction of corrosion pit depth and testing using neural network
You-qi chuyun
title Data augmentation using conditional generative adversarial network (cGAN): Application for prediction of corrosion pit depth and testing using neural network
title_full Data augmentation using conditional generative adversarial network (cGAN): Application for prediction of corrosion pit depth and testing using neural network
title_fullStr Data augmentation using conditional generative adversarial network (cGAN): Application for prediction of corrosion pit depth and testing using neural network
title_full_unstemmed Data augmentation using conditional generative adversarial network (cGAN): Application for prediction of corrosion pit depth and testing using neural network
title_short Data augmentation using conditional generative adversarial network (cGAN): Application for prediction of corrosion pit depth and testing using neural network
title_sort data augmentation using conditional generative adversarial network cgan application for prediction of corrosion pit depth and testing using neural network
url https://yqcy.pipechina.com.cn/cn/article/doi/
work_keys_str_mv AT xingyehuang dataaugmentationusingconditionalgenerativeadversarialnetworkcganapplicationforpredictionofcorrosionpitdepthandtestingusingneuralnetwork