TRACKING OF DRIVER ACTIVITY USING DEEP LEARNING

TRACKING OF DRIVER ACTIVITY USING DEEP LEARNING

Registration ID: IJNRD_204867

Published ID: IJNRD2309028

DOI: Click Here to Get

Dr.N.Usha Rani , K.Sravya

Feature extraction, Deep Learning, DenseNet, MobileNet, Convolutional Neural Networks.

Many traffic accidents worldwide are attributed to drivers who are not fully focused on the road, as they are engrossed in other activities. The behavior of drivers significantly impacts the safety of driving. However, existing methods that rely on image-based features to identify such behavior can sometimes misjudge critical situations. To comprehend driver actions, a system has been developed for recognizing driver activities, particularly distracted driving, using deep convolutional neural networks. This research suggests the utilization of DenseNet, MobileNet, and Convolutional Neural Networks (CNNs). The performance of DenseNet and MobileNet, both known for their lightweight design, is investigated across various datasets and network depths. Additionally, the quality of the dataset itself plays a pivotal role in determining the model's ability to make accurate generalizations. The ability to identify hazardous driving scenarios could prove valuable in reducing roadside accidents.

Published Paper   E-Certificate

"TRACKING OF DRIVER ACTIVITY USING DEEP LEARNING", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 9, page no.a231-a240, September-2023, Available :https://ijnrd.org/papers/IJNRD2309028.pdf

Volume 8 Issue 9, September-2023

Pages : a231-a240

Paper Reg. ID: IJNRD_204867

Published Paper Id: IJNRD2309028

Downloads: 000121156

Research Area: Computer Science & Technology 

Country: Tirupati, Andhra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2309028.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2309028

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

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