Modeling and Estimating LIDAR Intensity for Automotive Surfaces Using Gaussian Process Regression: An Experimental and Case Study Approach

Modeling and Estimating LIDAR Intensity for Automotive Surfaces Using Gaussian Process Regression: An Experimental and Case Study Approach

LIDAR technology is widely used in autonomous driving and environmental sensing, but its accuracy is significantly affected by variations in vehicle surface reflectivity. This study models and predicts the impact of different LIDAR sensor specifications and vehicle surface paints on laser intensity...

Full description

Saved in:
Bibliographic Details
Main Authors: Recep Eken, Oğuzhan Coşkun, Güneş Yılmaz
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
Subjects:
LIDAR intensity
surface reflectivity
machine learning
Gaussian process regression
Bayesian optimization
CUPAC dataset
Online Access:https://www.mdpi.com/2076-3417/15/6/2884
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2076-3417/15/6/2884

Similar Items