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...
Saved in:
| Main Authors: | Recep Eken, Oğuzhan Coşkun, Güneş Yılmaz |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/6/2884 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An informativeness score for optimal mixed datasets using Gaussian process regression
by: Cameron J LaMack, et al.
Published: (2025-01-01) -
Removal of LiDAR Negative Outliers Based on Retroreflective Surface
by: Haolong Gao, et al.
Published: (2025-01-01) -
ANALYSIS OF THE EXISTENCE OF THE AGRICULTURAL SECTOR IN MODELING POVERTY IN BENGKULU PROVINCE USING GAUSSIAN COPULA MARGINAL REGRESSION
by: Sigit Nugroho, et al.
Published: (2025-04-01) -
Enhancing Cutting Oil Efficiency with Nanoparticle Additives: A Gaussian Process Regression Approach to Viscosity and Cost Optimization
by: Beytullah Erdoğan, et al.
Published: (2025-06-01) -
Ship Hull Steel Plate Deformation Modeling Based on Gaussian Process Regression
by: Zhiliang Zhang, et al.
Published: (2024-12-01)