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http://dx.doi.org/10.17662/ksdim.2022.18.4.031

YOLOv4 Grid Cell Shift Algorithm for Detecting the Vehicle at Parking Lot  

Kim, Jinho (경일대학교 전자공학과)
Publication Information
Journal of Korea Society of Digital Industry and Information Management / v.18, no.4, 2022 , pp. 31-40 More about this Journal
Abstract
YOLOv4 can be used for detecting parking vehicles in order to check a vehicle in out-door parking space. YOLOv4 has 9 anchor boxes in each of 13x13 grid cells for detecting a bounding box of object. Because anchor boxes are allocated based on each cell, there can be existed small observational error for detecting real objects due to the distance between neighboring cells. In this paper, we proposed YOLOv4 grid cell shift algorithm for improving the out-door parking vehicle detection accuracy. In order to get more chance for trying to object detection by reducing the errors between anchor boxes and real objects, grid cells over image can be shifted to vertical, horizontal or diagonal directions after YOLOv4 basic detection process. The experimental results show that a combined algorithm of a custom trained YOLOv4 and a cell shift algorithm has 96.6% detection accuracy compare to 94.6% of a custom trained YOLOv4 only for out door parking vehicle images.
Keywords
YOLOv4; YOLO Custom Training; Vehicle Detection; Cell Shift Algorithm;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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