DAssd-Net: A Lightweight Steel Surface Defect Detection Model Based on Multi-Branch Dilated Convolution Aggregation and Multi-Domain Perception Detection Head

During steel production, various defects often appear on the surface of the steel, such as cracks, pores, scars, and inclusions. These defects may seriously decrease steel quality or performance, so how to timely and accurately detect defects has great technical significance. This paper proposes a l...

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Bibliographic Details
Main Authors: Ji Wang, Peiquan Xu, Leijun Li, Feng Zhang
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/23/12/5488