Pendeteksian Sepeda Motor Yang Melintasi Trotoar Menggunakan Algoritma YOLOv3

  • Eric Loudwyck Institut Teknologi dan Bisnis Kalbis
  • Yulia Ery Kurniawati Institut Teknologi dan Bisnis Kalbis
Keywords: convolutional neural network, object detection, traffic jam, yolov3


Indonesia ranks 10th as the most congested city in the world. To reduce traffic, private vehicle users have to switch to public transportation. When using public transportation, walking on the sidewalk is a common thing. However, the condition of pedestrian sidewalk sometimes become uncomfortable because there is a motorcyclist who crosses it due to traffic jams. This study aims to develop an application that can detect motorbikes crossing the sidewalk. So, it expects to reduce the number of motorcycle riders crossing the sidewalk. The method used in this study is YOLOv3 in the process of identifying motorcycles. The results of this study are software that can detect motorbikes crossing the sidewalk. By using YOLOv3, motorcycle detection can be carried out and produce video output with an average of 4 fps.


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