Journal of the Semiconductor & Display Technology (반도체디스플레이기술학회지)

The Korean Society Of Semiconductor & Display Technology (한국반도체디스플레이기술학회)
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Performance Comparison of Scaffold Defect Detection Model by Parameters

파라미터에 따른 인공지지체 불량 탐지 모델의 성능 비교

  • Song Yeon Lee (Department of Mechatronics Engineering, Graduate School of Korea University of Technology and Education) ;
  • Yong Jeong Huh (School of Mechatronics Engineering, Korea University of Technology and Education)
  • 이송연 (한국기술교육대학교 대학원 메카트로닉스공학과) ;
  • 허용정 (한국기술교육대학교 메카트로닉스공학부)
  • Received : 2023.03.02
  • Accepted : 2023.03.22
  • Published : 2023.03.31
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Abstract

In this study, we compared the detection accuracy of the parameters of the scaffold failure detection model. A detection algorithm based on convolutional neural network was used to construct a failure detection model for scaffold. The parameter properties of the model were changed and the results were quantitatively verified. The detection accuracy of the model for each parameter was compared and the parameter with the highest accuracy was identified. We found that the activation function has a significant impact on the detection accuracy, which is 98% for softmax.

Keywords

References

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