A multi-scale pooling convolutional neural network for accurate steel surface defects classification

A multi-scale pooling convolutional neural network for accurate steel surface defects classification

Surface defect detection is an important technique to realize product quality inspection. In this study, we develop an innovative multi-scale pooling convolutional neural network to accomplish high-accuracy steel surface defect classification. The model was built based on SqueezeNet, and experiments...

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Bibliographic Details
Main Authors: Guizhong Fu, Zengguang Zhang, Wenwu Le, Jinbin Li, Qixin Zhu, Fuzhou Niu, Hao Chen, Fangyuan Sun, Yehu Shen
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-02-01
Series:Frontiers in Neurorobotics
Subjects:
convolutional neural network
multi-scale
defect classification
class activation map
feature visualization
Online Access:https://www.frontiersin.org/articles/10.3389/fnbot.2023.1096083/full

Internet

https://www.frontiersin.org/articles/10.3389/fnbot.2023.1096083/full

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