산업경영시스템학회지 (Journal of Korean Society of Industrial and Systems Engineering)

  • 제44권3호
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  • Pages.1-9
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  • 2021
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  • 2005-0461(pISSN)
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  • 2287-7975(eISSN)
한국산업경영시스템학회 (Society of Korea Industrial and System Engineering)
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딥러닝 이미지 인식 기술을 활용한 소고기 등심 세부 부위 분류

Deep Learning based Image Recognition Models for Beef Sirloin Classification

  • 한준희 (동아대학교 산업경영공학과) ;
  • 정성훈 (동아대학교 산업경영공학과) ;
  • 박경수 (부산대학교 경영학과) ;
  • 유태선 (부경대학교 시스템경영공학부)
  • Han, Jun-Hee (Departement of Industrial & Management Systems Engineering, Dong-A University) ;
  • Jung, Sung-Hun (Departement of Industrial & Management Systems Engineering, Dong-A University) ;
  • Park, Kyungsu (Department of Business Administration, Pusan National University) ;
  • Yu, Tae-Sun (Division of Systems Management and Engineering, Pukyong National University)
  • 투고 : 2021.06.17
  • 심사 : 2021.08.09
  • 발행 : 2021.09.30
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초록

This research examines deep learning based image recognition models for beef sirloin classification. The sirloin of beef can be classified as the upper sirloin, the lower sirloin, and the ribeye, whereas during the distribution process they are often simply unified into the sirloin region. In this work, for detailed classification of beef sirloin regions we develop a model that can learn image information in a reasonable computation time using the MobileNet algorithm. In addition, to increase the accuracy of the model we introduce data augmentation methods as well, which amplifies the image data collected during the distribution process. This data augmentation enables to consider a larger size of training data set by which the accuracy of the model can be significantly improved. The data generated during the data proliferation process was tested using the MobileNet algorithm, where the test data set was obtained from the distribution processes in the real-world practice. Through the computational experiences we confirm that the accuracy of the suggested model is up to 83%. We expect that the classification model of this study can contribute to providing a more accurate and detailed information exchange between suppliers and consumers during the distribution process of beef sirloin.

키워드

과제정보

This work was supported by the Pukyong National University Research Fund in 2020(C-D-2020-0842). This work was also supported in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education under Grant 2020R1I1A3073672 and 2020R1G1A1099829. This research was also supported by the Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea Government (MOTIE: Ministry of Trade Industry and Energy; Grant No. N0002429).

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