A vehicle detection algorithm in complex traffic scenes

2020 ◽  
Author(s):  
Tianyu Jin ◽  
Dengyin Zhang ◽  
Fei Ding ◽  
Zhen Zhang ◽  
Min Zhang
Keyword(s):  
Vehicle Detection ◽  
Detection Algorithm

scholarly journals Vehicle detection algorithm based on LW-SSD

2021 ◽  
Vol 1748 ◽  
pp. 032042
Author(s):  
Yunxiang Liu ◽  
Guoqing Zhang
Keyword(s):  
Vehicle Detection ◽  
Detection Algorithm

scholarly journals Intelligent Highway Traffic Detection Algorithm based on Deep Learning

2021 ◽  
Author(s):  
ming ji ◽  
Chuanxia Sun ◽  
Yinglei Hu
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Traffic Congestion ◽  
Road Network ◽  
Vehicle Detection ◽  
Detection Algorithm ◽  
Recognition Algorithm ◽  
Traffic Data ◽  
Vehicle Recognition ◽  
Environment Recognition

Abstract In order to solve the increasingly serious traffic congestion problem, an intelligent transportation system is widely used in dynamic traffic management, which effectively alleviates traffic congestion and improves road traffic efficiency. With the continuous development of traffic data acquisition technology, it is possible to obtain real-time traffic data in the road network in time. A large amount of traffic information provides a data guarantee for the analysis and prediction of road network traffic state. Based on the deep learning framework, this paper studies the vehicle recognition algorithm and road environment discrimination algorithm, which greatly improves the accuracy of highway vehicle recognition. Collect highway video surveillance images in different environments, establish a complete original database, build a deep learning model of environment discrimination, and train the classification model to realize real-time environment recognition of highway, as the basic condition of vehicle recognition and traffic event discrimination, and provide basic information for vehicle detection model selection. To improve the accuracy of road vehicle detection, the vehicle target labeling and sample preprocessing of different environment samples are carried out. On this basis, the vehicle recognition algorithm is studied, and the vehicle detection algorithm based on weather environment recognition and fast RCNN model is proposed. Then, the performance of the vehicle detection algorithm described in this paper is verified by comparing the detection accuracy differences between different environment dataset models and overall dataset models, different network structures and deep learning methods, and other methods.

scholarly journals Scene-Adaptive Vehicle Detection Algorithm Based on a Composite Deep Structure

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 22804-22811 ◽  
Author(s):  
Yingfeng Cai ◽  
Hai Wang ◽  
Zhengyang Zheng ◽  
Xiaoqiang Sun
Keyword(s):  
Deep Structure ◽  
Vehicle Detection ◽  
Detection Algorithm
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