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Training method for vehicle detection

Title
Training method for vehicle detection
Author(s)
Kang, Min-SungLim, Young-Chul
Issued Date
2016
Citation
2nd International Conference on Communication and Information Processing, ICCIP 2016, pp.105 - 109
Type
Conference Paper
ISBN
9781450000000
Abstract
Recently, vehicle detection methods have been popularly used in the field of intelligent vehicles. The performance and processing time of vehicle detection is very important because it is associated with the life of a driver. However, all vehicle detection methods generate missing detections and false detections because of different vehicle appearances. However, in a general road environment, the appearance of most of these vehicles has a front and a rear. In this paper, we propose a training method to detect the front and rear of the vehicle. Our vehicle detection integrates state-of-the-art feature-based detection. © 2016 ACM.
URI
http://hdl.handle.net/20.500.11750/4333
DOI
10.1145/3018009.3018034
Publisher
Association for Computing Machinery
Related Researcher
  • 임영철 Lim, Young Chul
  • Research Interests Deep learning;딥러닝; object detection;객체검출; re-identification;재식별; multi-object tracking;다중객체추적; multi-camera video analysis;다중카메라영상분석
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Appears in Collections:
Division of Automotive Technology 2. Conference Papers

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