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 …

LiDAR-based 3D object detection models have traditionally struggled under rainy conditions
due to the degraded and noisy scanning signals. Previous research has attempted to …

Autonomous vehicles rely on LiDAR sensors to perceive the environment. Adverse weather
conditions like rain, snow, and fog negatively affect these sensors, reducing their reliability …

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 …

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 …

3D object detection (OD) is a crucial element in scene understanding. However, most
existing 3D OD models have been tailored to work with light detection and ranging (LiDAR) …

The perception systems of autonomous vehicles face significant challenges under adverse
conditions, with issues such as obscured objects and false detections due to environmental …

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 …