首页> 外文会议>IEEE Global Conference on Consumer Electronics >Robust Detection and Recognition of Japanese Traffic Sign in the Complex Scenes Based on Deep Learning
【24h】

Robust Detection and Recognition of Japanese Traffic Sign in the Complex Scenes Based on Deep Learning

机译:基于深度学习的复杂场景中日本交通标志的鲁棒检测与识别

获取原文

摘要

This study applies the object detection and recognition method using deep learning, which has been attracting considerable attention recently, for the detection and recognition of traffic signs. Furthermore, the advantages and disadvantages of the proposed method are discussed. During the detection and recognition of traffic signs, the following problems were identified. (1) The detection and recognition accuracy of a small object in an image, such as a distant road sign, was low. (2) The accuracy of the traffic sign detection and recognition was affected due to the changes in contrast at night and bad weather. Herein, we address these problems by learning the traffic signs through deep learning, which is robust against scale changes. Herein, we construct a Japanese traffic sign database and compared the methods used. Results demonstrate that the proposed approach demonstrates excellent detection and recognition accuracy.
机译:这项研究将基于深度学习的对象检测和识别方法应用于交通标志的检测和识别中,该方法最近受到了广泛的关注。此外,讨论了该方法的优缺点。在检测和识别交通标志期间,发现了以下问题。 (1)图像中小物体(例如远方路标)的检测和识别精度较低。 (2)由于夜间和恶劣天气下对比度的变化,交通标志检测和识别的准确性受到影响。本文中,我们通过深度学习来学习交通标志,从而解决了这些问题,这对于规模变化是很稳健的。在此,我们构建了一个日本交通标志数据库,并比较了所使用的方法。结果表明,所提出的方法证明了出色的检测和识别精度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号