We present a scheme of how YOLO can be improved in order to predict the absolute
distance of objects using only information from a monocular camera. It is fully integrated into …

Transformer and its variants have shown state-of-the-art results in many vision tasks
recently, ranging from image classification to dense prediction. Despite of their success …

Symmetric encryption algorithms enable rapid encryption of data in IoT based supply chains,
which helps to alleviate the concerns of supply chain participants about privacy disclosure …

The purpose of this study is to propose a framework for accurate and efficient vehicle
distance estimation from a monocular camera. The proposed framework consists of a …

Estimating traffic flow is essential in planning road development, routing, navigation,
autonomous driving, and other applications in road infrastructure management. Recently …

Within the context of smart transportation and new infrastructure, Vehicle-to-Everything
(V2X) communication has entered a new stage, introducing the concept of holographic …

The distance estimation of objects from a single camera can play a crucial role in many real-
life applications, such as mobile robot navigation, autonomous vehicles and camera-based …

Estimating a dense depth map from a single view is geometrically ill-posed, and state-of-the-
art methods rely on learning depth's relation with visual appearance using deep neural …

Lane detection is of critical importance to both the self-driving cars as well as advanced
driver assistance systems. While current methods use a range of features from low-level to …

Pedestrians are the most vulnerable road users, with around 23% of world road traffic
fatalities. To prevent such traffic collisions, the Pedestrian Collision Warning System (PCWS) …