Paper Title
CHAUFFEUR BEHAVIOR RECOGNITION BASED ON THE CONVOLUTION NEURAL SYSTEM
Article Identifiers
Authors
Raksha.M , Nimishambha Bharani S , Pushpa Yadav , Jayakumar B L
Keywords
behavior recognition, deep learning, maxpool, gabber filter, accident control, sleep detector
Abstract
Chauffeur behavior recognition is extensively used to lessen the threat of traffic accidents. maximum of the previous techniques for monitoring chauffeur's behavior is based on computer vision techniques. these strategies have the potential for invasion of privacy and spoofing. this text gives a brand new however effective deep studying approach for reading driving behavior using cues inclusive of facial expressions used to apprehend five forms of using: aggressive, distracted, drowsy, and drinking distraction.to make use of a successful deep neural network from snapshots, we study convolutional neural networks (CNNs) from photographs built from manipulated alerts based totally on the circular plot technique. As a result of the test, it changed into confirmed that the proposed technique can correctly detect the chauffeur's behavior.
Downloads
How To Cite
"CHAUFFEUR BEHAVIOR RECOGNITION BASED ON THE CONVOLUTION NEURAL SYSTEM", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 4, page no.c175-c186, April-2023, Available :https://ijnrd.org/papers/IJNRD2304222.pdf
Issue
Volume 8 Issue 4, April-2023
Pages : c175-c186
Other Publication Details
Paper Reg. ID: IJNRD_190908
Published Paper Id: IJNRD2304222
Downloads: 000121139
Research Area: Engineering
Country: Bangalore, Karnataka, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2304222.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2304222
About Publisher
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
Licence
This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition


Publication Timeline
Article Preview: View Full Paper
Call For Paper
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?
By Our website
Click Here to Submit Paper Online
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