Deep Learning Technique for Real-time Traffic Light Detection by Automated Vehicles

2018 ◽  
Vol 6 (7) ◽  
pp. 387-392
Author(s):  
Priyanka S.N. ◽  
Shashidhara H.S.
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Automated Vehicles ◽  
Traffic Light ◽  
Light Detection ◽  
Real Time Traffic ◽  
Learning Technique

A Real-Time Traffic Light Detection Algorithm Based on Adaptive Edge Information

2018 ◽  
Author(s):  
Guizhen Yu ◽  
Ao Lei ◽  
Honggang Li ◽  
Yunpeng Wang ◽  
Zhangyu Wang ◽  
...  
Keyword(s):  
Real Time ◽  
Detection Algorithm ◽  
Traffic Light ◽  
Light Detection ◽  
Edge Information ◽  
Real Time Traffic

scholarly journals Real Time Traffic Light Detection by Autonomous Vehicles using Artificial Neural Network Techniques

2019 ◽  
Vol 8 (10) ◽  
pp. 2129-2133
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Autonomous Vehicles ◽  
Traffic Light ◽  
Artificial Intelligence Technique ◽  
Light Detection ◽  
Traffic Lights ◽  
Real Time Traffic ◽  
The Right ◽  
Sufficient Precision

Autonomous vehicles are the reality of the future, they will open up the way for future advanced systems where computers are expected to take over the decision making of driving. These automobiles are capable of sensing their environment and moving with little or no human input. The main goal of this research is to detect traffic light in real-time for autonomous vehicles. Apart from taking decisions to navigate in the right manner the autonomous vehicles important task is to detect traffic lights, so that it can obey the traffic rules with sufficient precision. The work carried out in this research makes use of two Artificial Intelligence technique, these techniques are compared in accomplishing the task of traffic light detection in real time. The two models that are designed and implemented are Convolution neural network (CNN) and Deep Convolution Inverse Graphics Network (DCIGN). The results clearly show that DCIGN out performance CNN by 8%.

scholarly journals Parallelism Optimized Architecture on FPGA for Real-Time Traffic Light Detection

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 178167-178176
Author(s):  
Xue-Hua Wu ◽  
Renjie Hu ◽  
Yu-Qing Bao
Keyword(s):  
Real Time ◽  
Traffic Light ◽  
Light Detection ◽  
Real Time Traffic
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