相关论文: Turning Transport Data to Comply with EU Standards…

Advances in Data Science permeate every field of Transportation Science and Engineering, resulting in developments in the transportation sector that {are} data-driven. Nowadays, Intelligent Transportation Systems (ITS) could be arguably…

Parameter-efficient fine-tuning (PEFT) in multimodal tracking reveals a concerning trend where recent performance gains are often achieved at the cost of inflated parameter budgets, which fundamentally erodes PEFT's efficiency promise. In…

Intelligent Transportation Systems increasingly depend on heterogeneous data from roadside cameras, UAV imagery, LiDAR, and in-vehicle sensors, yet the lack of unified data standards, model interfaces, and evaluation protocols across these…

Product matching corresponds to the task of matching identical products across different data sources. It typically employs available product features which, apart from being multimodal, i.e., comprised of various data types, might be…

An increasing amount of information is generated from the rapidly increasing number of sensor networks and smart devices. A wide variety of sources generate and publish information in different formats, thus highlighting interoperability as…

Autonomous vehicles demand detailed maps to maneuver reliably through traffic, which need to be kept up-to-date to ensure a safe operation. A promising way to adapt the maps to the ever-changing road-network is to use crowd-sourced data…

Data Spaces are an emerging concept for the trusted implementation of data-based applications and business models, offering a high degree of flexibility and sovereignty to all stakeholders. As Data Spaces are currently emerging in different…

Predicting future trajectories of surrounding obstacles is a crucial task for autonomous driving cars to achieve a high degree of road safety. There are several challenges in trajectory prediction in real-world traffic scenarios, including…

Assuring safety of automated vehicles (SAE Level 3+) requires specifying and validating the behavior of such a vehicle in its operational environment. In order to argue and support assumptions that are made during the behavior specification…

Multi-head attention is appealing for its ability to jointly extract different types of information from multiple representation subspaces. Concerning the information aggregation, a common practice is to use a concatenation followed by a…

Intelligent transportation systems (ITS) have been developed to improve traffic flow, efficiency, and safety in transportation. Technological advancements in communication such as the Vehicle-to-Everything (V2X), Vehicle-to-Vehicle (V2V)…

Safe, environmentally conscious and flexible, these are the central requirements for the future mobility. In the European border region between Germany, France and Luxembourg, mobility in the world of work and pleasure is a decisive factor.…

This work proposes an open interoperable data portal that offers access to a Web-wide climate domain knowledge graph created for Ireland and England's NOAA climate daily data. There are three main components contributing to this data…

Achieving top-notch performance in Intelligent Transportation detection is a critical research area. However, many challenges still need to be addressed when it comes to detecting in a cross-domain scenario. In this paper, we propose a…

The creation of a next generation internet (semantic web) is impossible without attributes, allowing the semantic association of documents and their integration into information context. To achieve these goals, the Universal Metadata…

In the coming years, transportation system will be revamped in a manner that there will be more intelligent and autonomous vehicle phenomenon around us such as smart cars, auto driving system, etc. Some of automotive industries are already…

The NetMob Data Challenge releases a comprehensive public transportation dataset from Niter\'oi, addressing the lack of high-quality mobility and passenger demand data. Based on operational records from March 2026, the dataset combines four…

Text-to-Image (T2I) models have demonstrated their versatility in a wide range of applications. However, adaptation of T2I models to specialized tasks is often limited by the availability of task-specific data due to privacy concerns. On…

Semantic Communication (SEM-COM) has emerged as one of the disruptive technologies facilitating the evolution towards sixth-generation (6G) wireless networks. This article presents the potential of SEM-COM to transform Vehicle-to-Everything…

Multi-source Domain Adaptation (MDA) seeks to adapt models trained on data from multiple labeled source domains to perform effectively on an unlabeled target domain data, assuming access to sources data. To address the challenges of model…