반도체디스플레이기술학회지 (Journal of the Semiconductor & Display Technology)

한국반도체디스플레이기술학회 (The Korean Society Of Semiconductor & Display Technology)
권호 표지

CNN 기반 딥러닝을 이용한 인공지지체의 외형 변형 불량 검출 모델에 관한 연구

A Study on Shape Warpage Defect Detecion Model of Scaffold Using Deep Learning Based CNN

  • 이송연 (한국기술교육대학교대학원 메카트로닉스공학과) ;
  • 허용정 (한국기술교육대학교 메카트로닉스공학부)
  • Lee, Song-Yeon (Mechatronics Engineering, Graduate School of Korea University of Technology and Education) ;
  • Huh, Yong Jeong (Department of Mechatronics Engineering, Korea University of Technology and Education)
  • 투고 : 2021.03.12
  • 심사 : 2021.03.19
  • 발행 : 2021.03.31
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초록

Warpage defect detecting of scaffold is very important in biosensor production. Because warpaged scaffold cause problem in cell culture. Currently, there is no detection equipment to warpaged scaffold. In this paper, we produced detection model for shape warpage detection using deep learning based CNN. We confirmed the shape of the scaffold that is widely used in cell culture. We produced scaffold specimens, which are widely used in biosensor fabrications. Then, the scaffold specimens were photographed to collect image data necessary for model manufacturing. We produced the detecting model of scaffold warpage defect using Densenet among CNN models. We evaluated the accuracy of the defect detection model with mAP, which evaluates the detection accuracy of deep learning. As a result of model evaluating, it was confirmed that the defect detection accuracy of the scaffold was more than 95%.

키워드

참고문헌

  1. Song-Yeon Lee and Yong-Jeong Huh, "A Study on Prediction Model of Scaffold Pore Size Using Machine Learning", J. of The Korean Society of Semiconductor & Display Technology, Vol.18, pp. 46-50, 2019.
  2. Song-Yeon Lee and Yong-Jeong Huh, "A Study on Square Pore Shape Discrimination Model of Scaffold Using Machine Learning Based Multiple Linear Regression", J. of The Korean Society of Semiconductor & Display Technology, Vol.19, pp. 59-64, 2020.
  3. Sang-Ho Park, Joo-Hyeong Lee and Jung-Min Kim, "Development of Heating System for Ensuring Accuracy of Output for Open 3D Printer", J. of The Korean Society of Mechanical Engineers, Vol.41, pp. 477-482, 2017.
  4. Song-Yeon Lee and Yong-Jeong Huh, "A Study on Prediction Model Performance of Scaffold Pore Size Using Machine Learning Regression Method", J. of The Korean Society of Semiconductor & Display Technology, Vol.19, pp. 36-41, 2020.
  5. Yong-Hwan Lee and Heung-Jun Kim, "Implementation of Fish Detection Based on Convolution Neural Networks" J. of The Korea Society of Semiconductor & Display Technology, Vol.19, pp.124-129, 2020.
  6. Chang-Hee Yang, Kyu-Sub Park, Young-Sub Kim and Yong-Hwan Lee, "Comparative Analysis for Emotion Expression Using Three Methods Based by CNN" J. of The Korea Society of Semiconductor & Display Technology, Vol.19, pp.65-70, 2020.
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