Enhancing Precision with an Ensemble Generative Adversarial Network for Steel Surface Defect Detectors (EnsGAN-SDD)

Defects are the primary problem affecting steel product quality in the steel industry. The specific challenges in developing detect defectors involve the vagueness and tiny size of defects. To solve these problems, we propose incorporating super-resolution technique, sequential feature pyramid netwo...

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Bibliografski detalji

Glavni autori:	Fityanul Akhyar, Elvin Nur Furqon, Chih-Yang Lin
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2022-06-01
Serija:	Sensors
Teme:	defect detection generative adversarial network (GAN) recursive FPN boundary localization
Online pristup:	https://www.mdpi.com/1424-8220/22/11/4257
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