Human factors are a primary cause of vehicle accidents. Driver monitoring systems, utilizing
a range of sensors and techniques, offer an effective method to monitor and alert drivers to …

Encounters between humans and wildlife often lead to injuries, especially in remote
wilderness regions, and highways. Therefore, animal detection is a vital safety and wildlife …

Object detection is one of the vital and challenging tasks of computer vision. It supports a
wide range of applications in real life, such as surveillance, shipping, and medical …

Autonomous vehicles (AVs) are expected to play a key role in the future of transportation,
and to introduce a disruptive yet potentially beneficial change for wildlife–vehicle …

Deep Learning has grown in popularity as a method for solving computer vision difficulties.
Deep learning models are becoming increasingly efficient in solving complex real-world …

This paper uses virtual simulations to examine the interaction between autonomous vehicles
(AVs) and their surrounding environment. A framework was developed to estimate the …

The accurate and real-time detection of road lanes is crucial for the safe navigation of
autonomous vehicles (AVs). This paper presents a novel approach to lane detection by …

Obstacle detection is the most important functionality in the field of autonomous vehicles.
One of the common challenges is detecting a narrow driving lane and navigating through it …

In recent years, Autonomous Vehicles (AV) have transitioned from theoretical concepts to
tangible realities, largely due to significant advancements in sensor technologies, machine …

Autonomous vehicles (AV) are expected to play a key role in the future of transportation,
introduc-24 ing a disruptive yet potentially beneficial change for vehicle-wildlife interactions …