most citedMetamobility: Connecting Future Mobility with Metaverse

2 citations · 4 across the 7 of their papers we have counts for

collaborators

7 papers

cs.NI2023

Visualization of Mobility Digital Twin: Framework Design, Case Study, and Future Challenges

Yueyang Liu, Xiaolong Tu, Dawei Chen +4

A Mobility Digital Twin is an emerging implementation of digital twin technology in the transportation domain, which creates digital replicas for various physical mobility entities…

cs.CV2023

Confidence-based federated distillation for vision-based lane-centering

Yitao Chen, Dawei Chen, Haoxin Wang +2

A fundamental challenge of autonomous driving is maintaining the vehicle in the center of the lane by adjusting the steering angle. Recent advances leverage deep neural networks to…

math.NA2023★ 1 cited

A nearly optimal explicitly-sparse representation for oscillatory kernels with curvelet-like functions

Yanchuang Cao, Jun Liu, Dawei Chen

A nearly optimal explicitly-sparse representation for oscillatory kernels is presented in this work by developing a curvelet based method. Multilevel curvelet-like functions are co…

cs.LG2023

EPAM: A Predictive Energy Model for Mobile AI

Anik Mallik, Haoxin Wang, Jiang Xie +2

Artificial intelligence (AI) has enabled a new paradigm of smart applications -- changing our way of living entirely. Many of these AI-enabled applications have very stringent late…

cs.NI2023★ 1 cited

CoMap: Proactive Provision for Crowdsourcing Map in Automotive Edge Computing

Yongjie Xue, Yuru Zhang, Qiang Liu +2

Crowdsourcing data from connected and automated vehicles (CAVs) is a cost-efficient way to achieve high-definition maps with up-to-date transient road information. Achieving the ma…

cs.NI2023★ 2 cited

Metamobility: Connecting Future Mobility with Metaverse

Haoxin Wang, Ziran Wang, Dawei Chen +3

A Metaverse is a perpetual, immersive, and shared digital universe that is linked to but beyond the physical reality, and this emerging technology is attracting enormous attention…

cs.AI2022

Belief Acquisition as Stochastic Filtering

Dawei Chen, John Lloyd, Samuel Yang-Zhao +1

This paper studies how belief acquisition can be accomplished using stochastic filtering. First, a theoretical foundation for empirical beliefs is outlined. Then stochastic filteri…