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Author:

Wang, Zhili (Wang, Zhili.) | Yan, Hairong (Yan, Hairong.) | Zhou, Weiyu (Zhou, Weiyu.)

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EI Scopus

Abstract:

Defect detection in material micro-images has a significant impact on the study of the relationship between the micro-structure and macro-properties, however, material microdefects are usually relatively small and span a wide range of scales, which increases the difficulty of defect detection. Meanwhile, since defects exist in a small number, overfitting becomes another challenge. In this paper, based on the Faster R-CNN algorithm, automated data enhancement is used to solve the overfitting, and a feature pyramid model is proposed for the defects multi-scale problem, and finally, the feasibility of the above viewpoint is verified by experiments. © 2024 IEEE.

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Author Community:

  • [ 1 ] [Wang, Zhili]Beijing University of Technology, Software Engineering, Faculty of Information Technology, Beijing, China
  • [ 2 ] [Yan, Hairong]Beijing University of Technology, Software Engineering, Faculty of Information Technology, Beijing, China
  • [ 3 ] [Zhou, Weiyu]Beijing University of Technology, Software Engineering, Faculty of Information Technology, Beijing, China

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Year: 2024

Page: 696-699

Language: English

Cited Count:

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SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 4

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