A FUZZY BASED DEEP LEARNING MODEL TO IDENTIFY THE PATTERN RECOGNITION FOR LICENSED PLATES IN SMART VEHICLE MANAGEMENT SYSTEM
Abstract
vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff52532c000000021b060001000600
In general, vehicle management is based on the proper maintenance and safety of a vehicle. Based on this the quality of the vehicle is calculated. Most of the older vehicles are currently of poor quality and are producing high levels of pollution. Thus, it is necessary to find information about those vehicles. The number plate is helpful to find the information about the vehicle. In this paper, the number blood detection method is proposed. It is based on the fuzzy model and developed in the way of deep learning. Its main purpose is to provide accurate vehicle details from a given set of data. It has also been upgraded to provide its safety measures to its owner based on the vehicle data. Thus, this proposed model prevents major accidents. These functions can also be very helpful in recovering vehicles based on data from stolen vehicles.

Authors
B Chellapraba1, D Manohari2, M S Kavitha3, K Periyakaruppan4
Karpagam Institute of Technology, India1, St. Joseph’s Institute of Technology, India2, SNS College of Engineering, India3,4

Keywords
Vehicle Management, Fuzzy Model, Deep Learning, Number Plate
Yearly Full Views
JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember
011000000000
Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 12 , Issue: 3 , Pages: 2614-2618 )
Date of Publication :
April 2022
Page Views :
141
Full Text Views :
7

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.