MSAN-Net: An End-to-End Multi-Scale Attention Network for Universal Industrial Defect Detection

MSAN-Net: An End-to-End Multi-Scale Attention Network for Universal Industrial Defect Detection

With the rapid advancement of automation and intelligence in the electronics manufacturing industry, the throughput of a single production line was grown exponentially. Although high efficiency brought significant cost and time advantages, it also led to two major challenges: <xref ref-type="...

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Bibliographic Details
Main Authors: Zelu Wang, Ming Luo, Xinghe Xie, Yue Sun, Xinyu Tian, Zhengxuan Chen, Junwei Xie, Qinquan Gao, Tong Tong, Yue Liu, Tao Tan
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Industrial defect detection
visual transformer
deep learning
production automation
small object detection
Online Access:https://ieeexplore.ieee.org/document/11052274/
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