Enhancing AR/VR Performance via Optimized Edge-based Object Detection for Connected Autonomous Vehicles
Author:
Affiliation:
1. University of Houston,Electrical and Computer Engineering,Houston,TX,USA
2. Toyota Motor North America R&D,InfoTech Labs,Mountain View,CA,USA
3. The University of North Carolina at Charlotte,Electrical and Computer Engineering,Charlotte,NC,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10587320/10588370/10588561.pdf?arnumber=10588561
Reference12 articles.
1. Vetaverse: Technologies, applications, and visions toward the intersection of metaverse, vehicles, and transportation systems;Zhou,2022
2. Challenges and opportunities on AR/VR technologies for manufacturing systems in the context of industry 4.0: A state of the art review
3. AR-based Remote Command and Control Service: Self-driving Vehicles Use Case
4. Federated Learning for Object Detection in Autonomous Vehicles
5. FEVA: A Federated Video Analytics Architecture for Networked Smart Cameras
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