Search Results for author:
Found 4 papers, 0 papers with code
AugmenTory: A Fast and Flexible Polygon Augmentation Library
Data augmentation is a key technique for addressing the challenge of limited datasets, which have become a major component in the training procedures of image processing.
A Segment-Wise Gaussian Process-Based Ground Segmentation With Local Smoothness Estimation
Simulation results show the effectiveness of the proposed method to give a continuous and precise estimation of the ground surface in rough and bumpy scenes while being fast enough for real-world applications.
A Probabilistic Framework for Dynamic Object Recognition in 3D Environment With A Novel Continuous Ground Estimation Method
In this thesis a probabilistic framework is developed and proposed for Dynamic Object Recognition in 3D Environments.
A Novel Gaussian Process Based Ground Segmentation Algorithm with Local-Smoothness Estimation
The log-marginal likelihood function is assumed to be a multi-task objective function, to represent a whole-frame unbiased view of the ground at each frame.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
