Convolution neural network model with improved pooling strategy and feature selection for weld defect recognition

Convolution neural network model with improved pooling strategy and feature selection for weld defect recognition

Abstract Weld defect recognition plays an important role in the manufacturing process of large-scale equipment. Traditional methods generally include several serial steps, such as image preprocessing, region segmentation, feature extraction, and type recognition. The results of each s...

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Bibliographic Details
Main Authors: Jiang, Hongquan, Hu, Qihang, Zhi, Zelin, Gao, Jianmin, Gao, Zhiyong, Wang, Rongxi, He, Shuai, Li, Hua
Other Authors: Massachusetts Institute of Technology. Laboratory for Manufacturing and Productivity
Format: Article
Language:English
Published: Springer Berlin Heidelberg 2021
Online Access:https://hdl.handle.net/1721.1/136821

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