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Development of deep learning-based rock classifier for elementary, middle and high school education

  • Journal of Software Assessment and Valuation
  • Abbr : JSAV
  • 2019, 15(1), pp.63-70
  • DOI : 10.29056/jsav.2019.06.07
  • Publisher : Korea Software Assessment and Valuation Society
  • Research Area : Engineering > Computer Science
  • Received : May 29, 2019
  • Accepted : June 20, 2019
  • Published : June 30, 2019

Jina Park 1 Hwanseung Yong 1

1이화여자대학교

Candidate

ABSTRACT

These days, as Interest in Image recognition with deep learning is increasing, there has been a lot of research in image recognition using deep learning. In this study, we propose a system for classifying rocks through rock images of 18 types of rock(6 types of igneous, 6 types of metamorphic, 6 types of sedimentary rock) which are addressed in the high school curriculum, using CNN model based on Tensorflow, deep learning open source framework. As a result, we developed a classifier to distinguish rocks by learning the images of rocks and confirmed the classification performance of rock classifier. Finally, through the mobile application implemented, students can use the application as a learning tool in classroom or on-site experience.

Citation status

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