Defect segmentation algorithm for copper pipe soldering in X-ray images based on AM-TransUNet

In the X-ray digital images of soldered copper pipes with small diameters, the significant variations in size, shape, and contrast of soldering defect images make it difficult to achieve automatic defect recognition. To address this issue, an improved defect segmentation model, namely AM-TransUNet,...

ver descrição completa

Detalhes bibliográficos

Principais autores:	Lihua YANG, Jinxian ZHAO, Jinxiao LI, Haichun LIU, Qingsheng LI, Tao JIA, Dazhao CHI
Formato:	Artigo
Idioma:	Chinês
Publicado em:	Editorial Office of Transactions of the China Welding Institution, Welding Journals Publishing House 2025-07-01
Colecção:	Hanjie xuebao
Assuntos:	copper pipe with small diameter soldering defect x-ray testing deep learning defect segmentation
Acesso em linha:	https://doi.org/10.12073/j.hjxb.20241016001
Tags:	Adicionar Tag Sem tags, seja o primeiro a adicionar uma tag!