3 citations · 4 across the 11 of their papers we have counts for
12 papers
Dataset Safety in Autonomous Driving: Requirements, Risks, and Assurance
Alireza Abbaspour, Tejaskumar Balgonda Patil, B Ravi Kiran +2
Dataset integrity is fundamental to the safety and reliability of AI systems, especially in autonomous driving. This paper presents a structured framework for developing safe datas…
Evaluating the effect of data augmentation and BALD heuristics on distillation of Semantic-KITTI dataset
Anh Duong, Alexandre Almin, Léo Lemarié +1
Active Learning (AL) has remained relatively unexplored for LiDAR perception tasks in autonomous driving datasets. In this study we evaluate Bayesian active learning methods applie…
Self-Supervised 3D Monocular Object Detection by Recycling Bounding Boxes
Sugirtha T, Sridevi M, Khailash Santhakumar +4
Modern object detection architectures are moving towards employing self-supervised learning (SSL) to improve performance detection with related pretext tasks. Pretext tasks for mon…
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…
Rejection-Cascade of Gaussians: Real-time adaptive background subtraction framework
B Ravi Kiran, Arindam Das, Senthil Yogamani
Background-Foreground classification is a well-studied problem in computer vision. Due to the pixel-wise nature of modeling and processing in the algorithm, it is usually difficult…
Cost-complexity pruning of random forests
Kiran Bangalore Ravi, Jean Serra
Random forests perform bootstrap-aggregation by sampling the training samples with replacement. This enables the evaluation of out-of-bag error which serves as a internal cross-val…
Climbing on Pyramids
Jean Serra, Bangalore Ravi Kiran
A new approach is proposed for finding the "best cut" in a hierarchy of partitions by energy minimization. Said energy must be "climbing" i.e. it must be hierarchically and scale i…