Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …

Autonomous driving, in recent years, has been receiving increasing attention for its potential
to relieve drivers' burdens and improve the safety of driving. In modern autonomous driving …

Along with the massive growth of the Internet from the 1990s until now, various innovative
technologies have been created to bring users breathtaking experiences with more virtual …

Intelligent Automation (IA) in automobiles combines robotic process automation and artificial
intelligence, allowing digital transformation in autonomous vehicles. IA can completely …

Autonomous driving is regarded as one of the most promising remedies to shield human
beings from severe crashes. To this end, 3D object detection serves as the core basis of …

Autonomous vehicles require accurate, and fast decision-making perception systems to
know the driving environment. The 2D object detection is critical in allowing the perception …

In this paper, we aim at addressing two critical issues in the 3D detection task, including the
exploitation of multiple sensors (namely LiDAR point cloud and camera image), as well as …

Recently, the advancement of deep learning (DL) in discriminative feature learning from 3-D
LiDAR data has led to rapid development in the field of autonomous driving. However …

Driven by deep learning techniques, perception technology in autonomous driving has
developed rapidly in recent years, enabling vehicles to accurately detect and interpret …

The transportation detection of long-distance small objects has low accuracy. In this work,
we propose DMF, which is based on disparity depths. We map different disparity regions to …