Journal of the Semiconductor & Display Technology (반도체디스플레이기술학회지)

The Korean Society Of Semiconductor & Display Technology (한국반도체디스플레이기술학회)
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Implementation of Image Semantic Segmentation on Android Device using Deep Learning

딥-러닝을 활용한 안드로이드 플랫폼에서의 이미지 시맨틱 분할 구현

  • Lee, Yong-Hwan (Dept. of Digital Contents, Institute of Convergence and Creativity, Wonkwang University) ;
  • Kim, Youngseop (Dept. of Electronics and Electrical Engineering, Dankook University)
  • 이용환 (원광대학교 디지털콘텐츠공학과 융복합창의연구소) ;
  • 김영섭 (단국대학교 전자전기공학부)
  • Received : 2020.06.23
  • Accepted : 2020.06.24
  • Published : 2020.06.30
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Abstract

Image segmentation is the task of partitioning an image into multiple sets of pixels based on some characteristics. The objective is to simplify the image into a representation that is more meaningful and easier to analyze. In this paper, we apply deep-learning to pre-train the learning model, and implement an algorithm that performs image segmentation in real time by extracting frames for the stream input from the Android device. Based on the open source of DeepLab-v3+ implemented in Tensorflow, some convolution filters are modified to improve real-time operation on the Android platform.

Keywords

References

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