Traffic Sign Classification with a Convolutional Network

被引：4
|
作者：
Staravoitau A. [1 ]
机构：
[1] Belarusian State University, Minsk
来源：
Pattern Recognition and Image Analysis | 2018年 / 28卷 / 1期
关键词：
classification; convolutional network; GTSDB; machine learning; multi-scale features; TensorFlow; traffic signs;
D O I：
10.1134/S1054661818010182
中图分类号：
学科分类号：
摘要：
I approach the traffic signs classification problem with a convolutional neural network implemented in TensorFlow reaching 99.33% accuracy. The highlights of this solution would be data pre-processing, data augmentation pipeline, pre-training and skipping connections in the network. I am using Python as programming language and TensorFlow as a fairly low-level machine learning framework. © 2018, Pleiades Publishing, Ltd.
引用
收藏
页码：155 / 162
页数：7
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