• Title/Summary/Keyword: Deep lerning

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Rear-Approaching Vehicle Detection Research using Region of Interesting based on Faster R-CNN (Faster R-CNN 기반의 관심영역 유사도를 이용한 후방 접근차량 검출 연구)

  • Lee, Yeung-Hak;Kim, Joong-Soo;Shim, Jae-Chnag
    • Journal of IKEEE
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    • v.23 no.1
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    • pp.235-241
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    • 2019
  • In this paper, we propose a new algorithm to detect rear-approaching vehicle using the frame similarity of ROI(Region of Interest) based on deep learning algorithm for use in agricultural machinery systems. Since the vehicle detection system for agricultural machinery needs to detect only a vehicle approaching from the rear. we use Faster R-CNN model that shows excellent accuracy rate in deep learning for vehicle detection. And we proposed an algorithm that uses the frame similarity for ROI using constrained conditions. Experimental results show that the proposed method has a detection rate of 99.9% and reduced the false positive values.