3 citations · 3 across the 5 of their papers we have counts for
6 papers
LiDAR dataset distillation within bayesian active learning framework: Understanding the effect of data augmentation
Ngoc Phuong Anh Duong, Alexandre Almin, Léo Lemarié +1
Autonomous driving (AD) datasets have progressively grown in size in the past few years to enable better deep representation learning. Active learning (AL) has re-gained attention…
Exploring 2D Data Augmentation for 3D Monocular Object Detection
Sugirtha T, Sridevi M, Khailash Santhakumar +3
Data augmentation is a key component of CNN based image recognition tasks like object detection. However, it is relatively less explored for 3D object detection. Many standard 2D o…
Road Segmentation on low resolution Lidar point clouds for autonomous vehicles
Leonardo Gigli, B Ravi Kiran, Thomas Paul +4
Point cloud datasets for perception tasks in the context of autonomous driving often rely on high resolution 64-layer Light Detection and Ranging (LIDAR) scanners. They are expensi…
Deep Reinforcement Learning for Autonomous Driving: A Survey
B Ravi Kiran, Ibrahim Sobh, Victor Talpaert +4
With the development of deep representation learning, the domain of reinforcement learning (RL) has become a powerful learning framework now capable of learning complex policies in…
Regression and Classification by Zonal Kriging
Jean Serra, Jesus Angulo, B Ravi Kiran
Consider a family , of pairs of vectors and scalars that we aim to predict for a ne…
Multi-scale streaming anomalies detection for time series
B Ravi Kiran
In the class of streaming anomaly detection algorithms for univariate time series, the size of the sliding window over which various statistics are calculated is an important param…