Efficient Defect Classification Using Few-Shot Image Generation and Self-Attention Fused Convolution Features

Although deep learning has been proven to significantly outperform most traditional methods in the classification of large-scale balanced image datasets, collecting enough samples for defect classification is extremely time-consuming and costly. In this paper, we propose a lightweight defect classif...

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Detalhes bibliográficos

Principais autores:	Yingjie Zhang, Zhenwei Yang, Yue Xu, Yibo Ai, Weidong Zhang
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2024-06-01
coleção:	Applied Sciences
Assuntos:	defect classification few-shot generation attention mechanism feature fusion
Acesso em linha:	https://www.mdpi.com/2076-3417/14/12/5278
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