Elevating Driver Behavior Understanding With RKnD: A Novel Probabilistic Feature Engineering Approach-Reference-Cited by-同舟云学术

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Elevating Driver Behavior Understanding With RKnD: A Novel Probabilistic Feature Engineering Approach

Published:2024 Issue: Volume:12 Page:65780-65798
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Shariful Islam Mohammad¹^ORCID,Abu Tareq Rony Mohammad²,Safran Mejdl³^ORCID,Alfarhood Sultan³^ORCID,Che Dunren⁴^ORCID

Affiliation:

1. Department of Computer Science and Telecommunication Engineering, Noakhali Science and Technology University, Noakhali, Bangladesh

2. Department of Statistics, Noakhali Science and Technology University, Noakhali, Bangladesh

3. Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

4. School of Computing, Southern Illinois University, Carbondale, IL, USA

Funder

King Saud University, Riyadh, Saudi Arabia, through the Researchers

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10526235.pdf?arnumber=10526235

Reference38 articles.

1. The application of machine learning techniques for driving behavior analysis: A conceptual framework and a systematic literature review

2. Intelligent driver monitoring system: An Internet of Things-based system for tracking and identifying the driving behavior

3. Driver Behavior Analysis via Two-Stream Deep Convolutional Neural Network

4. Vehicle and Driver Monitoring System Using On-Board and Remote Sensors

5. Data-driven approaches for road safety: A comprehensive systematic literature review

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