The emergence of autonomous vehicles marks a transformative moment in the
transportation sector, significantly propelled by the integration of Light Detection and …

Accurately detecting power line defects under diverse weather conditions is crucial for
ensuring power grid reliability and safety. Existing power line inspection datasets, while …

LiDAR-based 3D object detectors have achieved unprecedented speed and accuracy in
autonomous driving applications. However, similar to other neural networks, they are often …

Although Light Detection and Ranging (LiDAR) is a sensor type for autonomous vehicles, it
is recognized as an essential tool in various fields, such as drones, Unmanned Surface …

Adverse weather conditions can severely affect the performance of LiDAR sensors by
introducing unwanted noise in the measurements. Therefore, differentiating between noise …

Adverse weather conditions such as snow, rain, and fog are natural phenomena that can
impair the performance of the perception algorithms in autonomous vehicles. Although …

LiDAR sensors are used in autonomous driving applications to accurately perceive the
environment. However, they are affected by adverse weather conditions such as snow, fog …

The complex traffic environment and various weather conditions make the collection of
LiDAR data expensive and challenging. Achieving high-quality and controllable LiDAR data …

Obstacle intrusion is a serious threat to the safety of railway traffic. LiDAR point cloud 3D
semantic segmentation (3DSS) provides a new method for unmanned rail-obstacle …

Autonomous vehicles rely on camera, LiDAR, and radar sensors to navigate the
environment. Adverse weather conditions like snow, rain, and fog are known to be …