Deep neural networks have revolutionized Machine Learning, completely reshaping several
domains of research in a mere decade. Domains like computer vision, for which deep …

Abstract Transport Mode Detection (TMD) is a classification problem where the goal is to
infer the transport mode of a user from GPS signals or inertial sensors, with applications …

Abstract In Transport Mode Detection, a great diversity of methodologies exist according to
the choice made on sensors, preprocessing, model used, etc. In this domain, the …

Transport mode detection is a classification problem aiming to design an algorithm that can
infer the transport mode of a user given multimodal signals (GPS and/or inertial sensors). It …

Ubiquitous and diverse sensors have enriched the transportation field with a multitude of
data types and substantial semantic knowledge, significantly advancing the development of …

The rapid growth of population and the permanent increase in the number of vehicles
engender several issues in transportation systems, which in turn call for an intelligent and …

In recent years, with the diversification of people's modes of transportation, a large amount of
traffic data is generated when people travel every day, and this data can help transportation …

Domain or statistical distribution shifts are a key staple of the wireless communication
channel, because of the dynamics of the environment. Deep learning (DL) models for …

The advancement of sensing technologies coupled with the rapid progress in big data
analysis has ushered in a new era in intelligent transport and smart city applications. In this …

Abstract Global Positioning System data plays a crucial role in comprehending an
individual's life due to its ability to provide geographic positions and timestamps. However …