Vehicle Number Plate Detection Using Machine Learning

Vehicle Number Plate Detection Using Machine Learning

Registration ID: IJNRD_194002

Published ID: IJNRD2305317

DOI: Click Here to Get

Rahmatullah , Achintya Sharma , Prof (Dr.) M Parthsarthi

Index Terms— Car plate Detection, deep neural network, license identification.

In this research, we look at detecting and recognizing car license plate problems in natural scene photographs. In a single forward transfer, here We introduce a deep neural network that could simultaneously locate license number plates and identify letters. The entire network could be trained from start to end. Unlike current techniques, which consider license plate detection and identification as two separate tasks that must be solved one at a time, our system incorporates the two tasks into one network that can solve them both simultaneously. It not only prevents intermediate errors from building up, but it also speeds up the processing. Four data sets containing photographs taken from different scenes under various conditions are evaluated for performance evaluation. Extensive tests demonstrate the efficacy and effectiveness of our suggested strategy.

Published Paper   E-Certificate

"Vehicle Number Plate Detection Using Machine Learning", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 5, page no.d109-d116, May-2023, Available :https://ijnrd.org/papers/IJNRD2305317.pdf

Volume 8 Issue 5, May-2023

Pages : d109-d116

Paper Reg. ID: IJNRD_194002

Published Paper Id: IJNRD2305317

Downloads: 000121113

Research Area: Computer Science & Technology 

Country: GAUTAM BUDDHA NAGAR, UTTAR PRADESH, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305317.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305317

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

IJNRD is Scholarly open access journals, Peer-reviewed, and Refereed Journals, High Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool), Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) with Open-Access Publications.

INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

Indexing In Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar | AI-Powered Research Tool, Microsoft Academic, Academia.edu, arXiv.org, Research Gate, CiteSeerX, ResearcherID Thomson Reuters, Mendeley : reference manager, DocStoc, ISSUU, Scribd, and many more

How to submit the paper?

Important Dates for Current issue

Paper Submission Open For: August 2025

Current Issue: Volume 10 | Issue 8

Last Date for Paper Submission: Till 31-Aug-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: International Peer-reviewed, Refereed, and Open Access Journal.

Subject Category: Research Area