235 citations · 850 across the 47 of their papers we have counts for
6 papers · 1 filter
Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance
Taylor Denouden, Rick Salay, Krzysztof Czarnecki +3
There is an increasingly apparent need for validating the classifications made by deep learning systems in safety-critical applications like autonomous vehicle systems. A number of…
Calibrating Uncertainties in Object Localization Task
Buu Phan, Rick Salay, Krzysztof Czarnecki +3
In many safety-critical applications such as autonomous driving and surgical robots, it is desirable to obtain prediction uncertainties from object detection modules to help suppor…
Urban Driving with Multi-Objective Deep Reinforcement Learning
Changjian Li, Krzysztof Czarnecki
Autonomous driving is a challenging domain that entails multiple aspects: a vehicle should be able to drive to its destination as fast as possible while avoiding collision, obeying…
Using Machine Learning Safely in Automotive Software: An Assessment and Adaption of Software Process Requirements in ISO 26262
Rick Salay, Krzysztof Czarnecki
The use of machine learning (ML) is on the rise in many sectors of software development, and automotive software development is no different. In particular, Advanced Driver Assista…
Clafer: Lightweight Modeling of Structure, Behaviour, and Variability
Paulius Juodisius, Atrisha Sarkar, Raghava Rao Mukkamala +3
Embedded software is growing fast in size and complexity, leading to intimate mixture of complex architectures and complex control. Consequently, software specification requires mo…
Unlimited Road-scene Synthetic Annotation (URSA) Dataset
Matt Angus, Mohamed ElBalkini, Samin Khan +5
In training deep neural networks for semantic segmentation, the main limiting factor is the low amount of ground truth annotation data that is available in currently existing datas…