Towards future intelligent vehicular network, the machine learning as the promising artificial
intelligence tool is widely researched to intelligentize communication and networking …

The ICDAR 2019 Challenge on" Scanned receipts OCR and key information
extraction"(SROIE) covers important aspects related to the automated analysis of scanned …

Road accidents and traffic congestion are two critical problems for global transport systems.
Connected vehicles (CV) and automated vehicles (AV) are among the most heavily …

In an urban environment, intersections are critical locations in terms of road crashes and
number of killed or injured people. Vehicular ad hoc networks (VANETs) can help reduce …

Vehicle Safety Communications (VSC) is advancing rapidly towards product development
and field testing. While a number of possible solutions have been proposed, the question …

The emergence of Vehicular Ad Hoc Networks (VANETs) is expected to be an important step
toward achieving safety and efficiency in intelligent transportation systems (ITS). One …

Federated Learning (FL) is a novel distributed machine learning which allows thousands of
edge devices to train model locally without uploading data concentrically to the server. But …

Vehicular communication requires vehicles to self-organize through the exchange of
periodic beacons. Recent analysis on beaconing indicates that the standards for beaconing …

In this letter, we investigate the distributed autonomous resource selection for LTE vehicle to
vehicle (V2V) broadcast. The effectiveness of collision avoidance and location based …

Federated Learning (FL) is a novel distributed machine learning, which allows thousands of
edge devices to train models locally without uploading data to the central server. Since …