In the context of automated driving, navigating through challenging urban environments with
dynamic objects, large-scale scenes, and varying lighting/weather conditions, achieving …

Object detection is an essential computer vision task that identifies and locates objects
within images or videos and is crucial for applications such as autonomous driving, robotics …

Over the last decades, deep neural networks (DNNs) have penetrated all fields of science
and the real world. As a result of the lack of quantifiable data and model uncertainty, deep …

Obeject detection as a fundamental task of environmental perception systems in
autonomous vehicles (AVs), is significant for intelligent driving safety that precise detection …

Three dimensional (3D) object detection using the camera and light detection and ranging
(LiDAR) fusion model has received much attention for meeting the environmental sensing …

LiDAR-Camera fusion-based 3D object detection is one of the main visual perception tasks
in autonomous driving, facing the challenges of small targets and occlusions. Image …

Abstract Vision-based three-dimensional (3D) situational awareness is undoubtedly the
most promising means to help autonomous ships solve the problem of visual perception …

Recent advancements in 3D object detection using light detection and ranging (LiDAR)-
camera fusion have enhanced autonomous driving perception. However, aligning LiDAR …

Pedestrian safety is a major concern in urban areas, and crosswalks are one of the most
critical locations where accidents can occur. This research introduces an intelligent …

Detecting objects in 3D space using LiDAR is crucial for robotics and autonomous vehicles,
but the sparsity of LiDAR-generated point clouds limits performance. Camera images, rich in …