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.
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How To Cite (APA)
Raksha.M, Nimishambha Bharani S, Pushpa Yadav, & Jayakumar B L (April-2023). CHAUFFEUR BEHAVIOR RECOGNITION BASED ON THE CONVOLUTION NEURAL SYSTEM. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(4), c175-c186. 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: 000121979
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
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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