Research and design of traffic recognition system based on Hilens

2021 ◽  
Author(s):  
HaoBo Lv ◽  
XueMing Dang ◽  
DingYi Yang ◽  
QingXiang Zhu
Keyword(s):  
Recognition System ◽  
Traffic Recognition ◽  
Research And Design

Research and Design of License Plate Recognition System

2014 ◽  
Vol 556-562 ◽  
pp. 2623-2627
Author(s):  
Feng Ran ◽  
Fa Yu Zhang ◽  
Mei Hua Xu
Keyword(s):  
Adaptive Learning ◽  
Character Recognition ◽  
Complete System ◽  
Recognition System ◽  
Morphological Processing ◽  
Character Segmentation ◽  
License Plate ◽  
License Plate Recognition ◽  
Research And Design ◽  
Speed And Accuracy

Introduce a complete system of license plate recognition: using morphological processing and priori knowledge of license plate to discern the location of license plate, accomplishing tilt correction through Radon transform, then fulfilling character segmentation of accurate positioning license plate by projection, finishing character recognition through BP neural network which was improved by the use of adaptive learning rate and momentum factor. With the programming and verification on Matlab experimental platform, experimental results show that we can have a preferable recognition speed and accuracy.

scholarly journals Transfer Learning Based Traffic Sign Recognition System for Surveillance Application

2019 ◽  
Vol 8 (3) ◽  
pp. 573-576
Keyword(s):  
Transfer Learning ◽  
Road Traffic ◽  
Recognition System ◽  
Vehicle Tracking ◽  
Traffic Sign Recognition ◽  
Traffic Sign ◽  
Sign Recognition ◽  
Wide Range ◽  
Traffic Recognition ◽  
Surveillance Application

Road Traffic Recognition is very important in many applications, such as automated deployment, traffic mapping, and vehicle tracking. Proposed traffic sign recognition system tails the transfer learning method that is frequently used in neural network uses. The benefit of expending this technique is that the initially network has been trained with a rich set of features appropriate to a wide range of images. Once the network is trained , learning can be transferred to the new activity adjustment to the network. Firsthand Indian traffic sign dataset is used.New results exhibit that the suggested method can accomplish modest outcomes when matched with other related techniques.

Research and Design of the License Plate Recognition Systems Based on ARM S3C2440

2013 ◽  
Vol 333-335 ◽  
pp. 2484-2488
Author(s):  
Zhen Tao Qin ◽  
Wu Nian Yang ◽  
Ru Yang
Keyword(s):  
Real Time ◽  
Intelligent Transportation ◽  
Recognition System ◽  
Experimental Results ◽  
Dynamic Monitoring ◽  
License Plate ◽  
License Plate Recognition ◽  
Hough Transformation ◽  
Recognition Systems ◽  
Research And Design

In order to meet the need of real-time and dynamic monitoring of intelligent transportation, a License Plate Recognition (LPR) System Based on ARM S3C2440 is introduced and a vehicle license recognition system is designed and realized. This thesis comparatively explains the tasks and problems and dose analytic research across all phases of the system. Image binary and slant rectification also be discussed, which are difficulty points in LPR. According to the study of the license plate images, we use hough transformation and image reverse rotation , a inclined rectification method was proposed. The experimental results show that the approach is excellent in the accuracy with rapid speed and is in the robustness.

Design and Implementation of Service Traffic Awareness System in LTE Network

2014 ◽  
Vol 644-650 ◽  
pp. 2902-2905
Author(s):  
Jian Wang ◽  
Zhi Zhong Zhang ◽  
Yun Long Luo
Keyword(s):  
Monitoring System ◽  
User Behavior ◽  
Mobile Network ◽  
Recognition System ◽  
Identification System ◽  
Deep Packet Inspection ◽  
Lte Network ◽  
Traffic Awareness ◽  
Traffic Recognition ◽  
Packet Inspection

Based on telecom operators increasingly urgent demand for intelligent pipeline, this paper has proposed a kind of implementing scheme of traffic recognition system in LTE network. Aiming at the traditional monitoring system with poor user perception and insufficient statistical capacity, we achieved a self - learning refining identification system of application layer services, and further analyzed the characteristic of user behavior in mobile network which relying on the traditional monitoring system and applying current prevailing Internet behavior analysis technologies-deep packet inspection (DPI) technique and focused crawler technology.

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