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 …

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

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 …

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 …

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 …

This thesis explores the transformative potential of deep learning smartphone-based
transportation mode detection systems in enhancing urban planning in the city of Barcelona …

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

Transportation Mode Identification (TMI) has been studied for over 10 years, but few
researches focused on datasets sampled at low sampling rates with low localization rates as …

Transportation is a significant component of human lives and understanding how individuals
travel is an essential task in many fields. Understanding the modes of transport individuals …

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 …