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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/30378
Title: Traffic sign detection and problems in the field of computer vision
Authors: Lukashevich, M.
Keywords: материалы конференций
object detection
deep learning
R-CNN
intelligent system
computer vision
Issue Date: 2018
Publisher: БГУИР
Citation: Lukashevich, M. Traffic sign detection and problems in the field of computer vision / M. Lukashevich // Открытые семантические технологии проектирования интеллектуальных систем = Open Semantic Technologies for Intelligent Systems (OSTIS-2018) : материалы международной научно-технической конференции (Минск, 15 - 17 февраля 2018 года) / редкол. : В. В. Голенков (отв. ред.) [и др.]. – Минск : БГУИР, 2018. – С. 235 - 238.
Abstract: Object detection is a typical task of computer vision. This paper presents some results of implementation of the traffic sign recognition. We use R-CNN for traffic sign detection system. We focus on speed limit superclasses of traffic sign. R-CNN deep learning detector is a simple and suitable model for the traffic sign recognition. This approach combines multiple low-level image features with high-level context from object detectors and scene classifiers. Despite the existing advances in computer vision, the article considers the problems that exist and which need to be solved in the future in the field of computer vision system design.
URI: https://libeldoc.bsuir.by/handle/123456789/30378
Appears in Collections:OSTIS-2018

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