Weld defect classification in radiographic images using unified deep neural network with multi-level features
Deep neural network (DNN) exhibits state-of-the-art performance in many fields including weld defect classification. However, there is still a large room for improving the classification performance over the generic DNN models. In this paper, a unified deep neural network with multi-level features i...
Main Authors: | Yang, Lu (Author), Jiang, Hongquan (Author) |
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Other Authors: | Massachusetts Institute of Technology. Laboratory for Manufacturing and Productivity (Contributor) |
Format: | Article |
Language: | English |
Published: |
Springer Science and Business Media LLC,
2021-02-11T21:57:34Z.
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Subjects: | |
Online Access: | Get fulltext |
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