For autonomous driving, perception is a primary and essential element that fundamentally
deals with the insight into the ego vehicle's environment through sensors. Perception is …

Autonomous vehicles rely on a variety of sensors to gather information about their
surrounding. The vehicle's behavior is planned based on the environment perception …

Images captured in low-light conditions present significant challenges for accurate object
detection due to factors such as high noise, poor illumination, and low contrast. In this study …

In an autonomous driving system, perception-identification of features and objects from the
environment-is crucial. In autonomous racing, high speeds and small margins demand rapid …

This study presents an adaptation of the YOLOv4 deep learning algorithm for 3D object
detection, addressing a critical challenge in autonomous vehicle (AV) systems: accurate real …

The development of safe and reliable autonomous unmanned aerial vehicles relies on the
ability of the system to recognise and adapt to changes in the local environment based on …

Recently there has been an increase in the number of available autonomous vehicle (AV)
models. To evaluate and compare the safety of the various models the AVs need to be …

Segmenting each moving object instance in a scene is essential for many applications. But
like many other computer vision tasks, this task performs well in optimal weather, but then …

Deep Learning (DL) based classification of conventional objects using mm-Wave Frequency
Modulated Continuous Wave (FMCW) radars is useful for multiple real-world automotive …

Classification of objects using radars can be useful for a wide range of applications
including surveillance systems, autonomous vehicles and collision avoidance systems for …