The Covid-19 pandemic has galvanized scientists to apply machine learning methods to
help combat the crisis. Despite the significant amount of research there exists no …

Lately, Autonomous vehicles (AV) have been gaining traction globally owing to their huge
social, economic and environmental benefits. However, the rising safety apprehensions for …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

The maritime Internet of Things (IoT) has recently emerged as a revolutionary
communication paradigm where a large number of moving vessels are closely …

Accurately predicting translation initiation sites (TIS) from genomic sequences is crucial for
understanding gene regulation and function. TIS prediction methods' feature vectors are not …

Predicting the future trajectories of pedestrians is a challenging problem that has a range of
application, from crowd surveillance to autonomous driving. In literature, methods to …

Trajectory prediction aims to predict the movement trend of the agents like pedestrians,
bikers, vehicles. It is helpful to analyze and understand human activities in crowded spaces …

Predicting human motion is a critical requirement in various applications, with particular
significance in the construction sector. This task presents significant challenges due to the …

Modelling the movement uncertainty of crowdsourced human trajectories in complex urban
areas is useful for various human mobility analytics and applications. However, the existing …

The aim of this paper is to synthesize and analyze existing evidence on connected vehicle
technologies, autonomous driving perception algorithms, and smart sustainable urban …