Road sign recognition with Convolutional Neural Network

Amal Bouti, Mohamed Adnane Mahraz, J. Riffi, H. Tairi
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引用次数: 4

Abstract

Extracting the contents of a digital image has been proven a hard problem for computers. Since for them, an image is only a matrix of values, knowing what structures a human would recognize in this image, is a nontrivial problem. In this paper, we have implemented and tested a system of detection of road signs. The approach taken in this work consists of using convolutional neural network where this network is supposed to distinguish between different classes of signs (stop, attention etc.) and the final model will then be integrated to the autonomous cars. Tests carried out on the dataset GTSRB (The German Traffic Sign Recognition Benchmark) shows the performance of the system currently being developed.
基于卷积神经网络的道路标志识别
对计算机来说,提取数字图像的内容已被证明是一个难题。因为对他们来说,图像只是一个值的矩阵,知道人类会在这个图像中识别出什么结构,是一个重要的问题。在本文中,我们实现并测试了一个道路标志检测系统。在这项工作中采用的方法包括使用卷积神经网络,该网络应该区分不同类别的标志(停止,注意等),然后最终模型将集成到自动驾驶汽车中。在数据集GTSRB(德国交通标志识别基准)上进行的测试显示了当前正在开发的系统的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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