Abstract Within the Beyond 6th Generation (B6G) network, this research presents an efficient
Convolutional Neural Network (CNN) architecture specifically tailored for image processing …

Advances in Artificial intelligence (AI) and embedded systems have resulted on a recent
increase in use of image processing applications for smart cities' safety. This enables a cost …

In recent years, deep learning strategies started to outshine traditional machine learning
methods in a few fields, with Computer Vision being one of the most noticeable ones. The …

This study proposes a simple convolutional neural network (CNN)-based model for vehicle
classification in low resolution surveillance images collected by a standard security camera …

The need for a smart city is more pressing today due to the recent pandemic, lockouts,
climate changes, population growth, and limitations on availability/access to natural …

Resumen The Digital Age has caused a rapid shift from traditional industry to an economy
mainly based upon information technology. According to recent studies, 74 zettabytes (ZB) …

In model cities, managing traffic flow is paramount, particularly during peak hours and festive
periods. Accurate and real-time traffic information is crucial for effective urban planning and …

Smart city applications covering a wide area such as traffic monitoring and pothole detection
are gradually adopting more image machine learning algorithms utilizing ubiquitous camera …

Recently, with the increasing complexity of urban environments, the need for advanced
technologies to ensure safe transportation in smart cities has become paramount. It has …

Increasing attention is being given to the application of machine learning such as deep
learning to image analysis. Aiming to provide a solution to social issues in urban areas, we …