Metallographic image segmentation of GCr15 bearing steel based on CGAN

doi:10.3233/JAE-209441

CORC > 兰州理工大学 > 兰州理工大学 > 机电工程学院

	Metallographic image segmentation of GCr15 bearing steel based on CGAN
	Chen, Yuanyuan 1; Jin, Wuyin 1; Wang, Meng 2
刊名	INTERNATIONAL JOURNAL OF APPLIED ELECTROMAGNETICS AND MECHANICS
	2020
卷号	64 期号:1-4 页码:1237-1243
关键词	Metallographic image image processing carbide particle segmentation deep learning CGAN
ISSN号	1383-5416
DOI	10.3233/JAE-209441
英文摘要	A novel deep learning segmentation method based on Conditional Generative Adversarial Nets (CGAN) is proposed, being U-GAN in this paper to overtake shortcomings of the metallographic images of GCr15 bearing steel, such as multi-noise, low contrast and difficult to segment. The results of experiment indicate that the proposed model is the most accurate comparing with the digital image processing methods and deep learning methods on carbide particle segmentation. The average Dice's coefficient of similarity measure function is 0.9158, which is the state-of-the-art performance on dataset.
WOS研究方向	Engineering ; Mechanics ; Physics
语种	英语
出版者	IOS PRESS
WOS记录号	WOS:000600069600142
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/155254]
专题	机电工程学院
作者单位	1.Lanzhou Univ Technol, Sch Mech & Elect Engn, Lanzhou, Gansu, Peoples R China; 2.Soochow Univ, Sch Elect & Informat Engn, Suzhou, Jiangsu, Peoples R China
推荐引用方式 GB/T 7714	Chen, Yuanyuan,Jin, Wuyin,Wang, Meng. Metallographic image segmentation of GCr15 bearing steel based on CGAN[J]. INTERNATIONAL JOURNAL OF APPLIED ELECTROMAGNETICS AND MECHANICS,2020,64(1-4):1237-1243.
APA	Chen, Yuanyuan,Jin, Wuyin,&Wang, Meng.(2020).Metallographic image segmentation of GCr15 bearing steel based on CGAN.INTERNATIONAL JOURNAL OF APPLIED ELECTROMAGNETICS AND MECHANICS,64(1-4),1237-1243.
MLA	Chen, Yuanyuan,et al."Metallographic image segmentation of GCr15 bearing steel based on CGAN".INTERNATIONAL JOURNAL OF APPLIED ELECTROMAGNETICS AND MECHANICS 64.1-4(2020):1237-1243.