Road accidents are increasing worldwide and are causing millions of deaths each year.
They impose significant financial and economic expenses on society. Existing research has …

This study evaluates the impact of large language models on enhancing machine learning
processes for managing traffic incidents. It examines the extent to which features generated …

Road Traffic Accidents (RTA) cause human losses and irreparable physical and
psychological damage to many of the victims. They also involve a very relevant economic …

This research showcases the innovative integration of Large Language Models into
machine learning workflows for traffic incident management, focusing on the classification of …

In-memory computing (IMC) is an effective approach to accelerate the interference tasks of
binary neural networks (BNN), which has been widely used in artificial intelligence of things …

Autonomous vehicles (AVs) represent an exciting frontier in transportation, promising
increased safety and efficiency on the roads. However, like any technological advancement …

Traffic accidents are becoming a global issue, causing enormous losses in both human and
financial resources. According to a World Health Organization assessment, the severity of …

In the present work, the possibility of preventing damage to cars and increasing the safety of
cars using Image Processing has been explored. A method for modifying an image to …

Modern infrastructure systems are grappling with increased complexity and
interdependence, struggling to predict and manage failures amid factors like population …

The use of speech-based recognition technologies in human–computer interactions is
increasing daily. Age and gender recognition, one of these technologies, is a popular …