104 citations · 447 across the 17 of their papers we have counts for
17 papers
Out-of-Distribution Detection for LiDAR-based 3D Object Detection
Chengjie Huang, Van Duong Nguyen, Vahdat Abdelzad +5
3D object detection is an essential part of automated driving, and deep neural networks (DNNs) have achieved state-of-the-art performance for this task. However, deep models are no…
A Safety Assurable Human-Inspired Perception Architecture
Rick Salay, Krzysztof Czarnecki
Although artificial intelligence-based perception (AIP) using deep neural networks (DNN) has achieved near human level performance, its well-known limitations are obstacles to the…
If a Human Can See It, So Should Your System: Reliability Requirements for Machine Vision Components
Boyue Caroline Hu, Lina Marsso, Krzysztof Czarnecki +3
Machine Vision Components (MVC) are becoming safety-critical. Assuring their quality, including safety, is essential for their successful deployment. Assurance relies on the availa…
Robustifying Controller Specifications of Cyber-Physical Systems Against Perceptual Uncertainty
Tsutomu Kobayashi, Rick Salay, Ichiro Hasuo +3
Formal reasoning on the safety of controller systems interacting with plants is complex because developers need to specify behavior while taking into account perceptual uncertainty…
The missing link: Developing a safety case for perception components in automated driving
Rick Salay, Krzysztof Czarnecki, Hiroshi Kuwajima +6
Safety assurance is a central concern for the development and societal acceptance of automated driving (AD) systems. Perception is a key aspect of AD that relies heavily on Machine…
The Effect of Optimization Methods on the Robustness of Out-of-Distribution Detection Approaches
Vahdat Abdelzad, Krzysztof Czarnecki, Rick Salay
Deep neural networks (DNNs) have become the de facto learning mechanism in different domains. Their tendency to perform unreliably on out-of-distribution (OOD) inputs hinders their…