Green-Tech CAV: Next Generation Computing for Traffic Sign and Obstacle Detection in Connected and Autonomous Vehicles-Reference-Cited by-同舟云学术

Green-Tech CAV: Next Generation Computing for Traffic Sign and Obstacle Detection in Connected and Autonomous Vehicles

Published:2022-09 Issue:3 Volume:6 Page:1307-1315
ISSN:2473-2400
Container-title:IEEE Transactions on Green Communications and Networking
language:
Short-container-title:IEEE Trans. on Green Commun. Netw.

Author:

Kumar V. D. Ambeth¹^ORCID,Raghuraman Manish¹,Kumar Abhishek²,Rashid Mamoon³^ORCID,Hakak Saqib⁴^ORCID,Reddy M. Praveen Kumar⁵

Affiliation:

1. Department of Computer Science and Engineering, Panimalar Engineering College, Anna University, Chennai, India

2. Department of Communication and Media Design, School of Creative Media and Design, and the Department of Animation and Virtual Reality, School of Computer Science and IT, JAIN (Deemed-to-be University), Bengaluru, India

3. Department of Computer Engineering, Faculty of Science and Technology, Vishwakarma University, Pune, India

4. Canadian Institute for Cybersecurity, Faculty of Computer Science, University of New Brunswick, Fredericton, NB, Canada

5. Department of Information Technology, Vellore Institute of Technology, Vellore, India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Renewable Energy, Sustainability and the Environment

Link

http://xplorestaging.ieee.org/ielx7/7511293/9863718/09743566.pdf?arnumber=9743566

Reference43 articles.

1. A Hybrid Deep Reinforcement Learning For Autonomous Vehicles Smart-Platooning

2. Robust Lane Detection and Tracking for Real-Time Applications

3. Detecting symbols on road surface for mapping and localization using OCR

4. BoxCars: 3D Boxes as CNN Input for Improved Fine-Grained Vehicle Recognition

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