Deep neural networks have become prevalent in human analysis, boosting the performance
of applications, such as biometric recognition, action recognition, as well as person re …

Synthetic datasets, for which we propose the term synthsets, are not a novelty but have
become a necessity. Although they have been used in computer vision since 1989, hel** …

A large field-of-view fisheye camera allows for capturing a large area with minimal numbers
of cameras when they are mounted on a high position facing downwards. This topview …

In recent years, there has been a growing interest in synthetic data for several computer
vision applications, such as automotive, detection and tracking, surveillance, medical image …

The current sanitary emergency situation caused by COVID-19 has increased the interest in
controlling the flow of people in indoor infrastructures, to ensure compliance with the …

In today's competitive marketplace, businesses face the ongoing challenge of meeting
evolving customer demands while maintaining sustainable practices. For airlines …

Deep learning has transformed data generation, particularly in creating synthetic sensor
data. This capability is invaluable in fields like autonomous driving, robotics, and computer …

Global demographic shifts have led to more cases of cognitive impairment, such as amnestic
mild cognitive impairment (aMCI), which typically involves memory loss and disorientation …

Deep neural network (DNN)-based vision systems could improve passenger transportation
safety by automating processes such as verifying the correct positioning of luggage, seat …

The latest advances in Deep Learning allow for increasing the automation and safety of
driving systems. However, the shortage of openly available railway datasets makes it difficult …