A Deep Learning Model of Traffic Signs in Panoramic Images Detection

作     者：Kha Tu Huynh Thi Phuong Linh Le Muhammad Arif Thien Khai Tran 

作者机构：International UniversityHo Chi Minh CityVietnam-Vietnam National UniversityHo Chi Minh City700000Vietnam Department of Computer ScienceThe Superior UniversityLahorePakistan Ho Chi Minh City University of Foreign Languages and Information TechnologyHo Chi Minh City700000Vietnam 

出 版 物：《Intelligent Automation & Soft Computing》 (智能自动化与软计算（英文）)

年 卷 期：2023年第37卷第7期

页      面：401-418页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

主　　题：Deep learning convolutional neural network Mask R-CNN traffic signs detection 

摘      要：To pursue the ideal of a safe high-tech society in a time when traffic accidents are frequent,the traffic signs detection system has become one of the necessary topics in recent years and in the *** ultimate goal of this research is to identify and classify the types of traffic signs in a panoramic *** accomplish this goal,the paper proposes a new model for traffic sign detection based on the Convolutional Neural Network for com-prehensive traffic sign classification and Mask Region-based Convolutional Neural Networks(R-CNN)implementation for identifying and extracting signs in panoramic *** augmentation and normalization of the images are also applied to assist in classifying better even if old traffic signs are degraded,and considerably minimize the rates of discovering the extra *** proposed model is tested on both the testing dataset and the actual images and gets 94.5%of the correct signs recognition rate,the classification rate of those signs discovered was 99.41%and the rate of false signs was only around 0.11.