Search Results for author: Kerstin Eder

Found 12 papers, 2 papers with code

Trustworthiness Score to Evaluate CNNs Predictions

no code implementations21 Jan 2023 Abanoub Ghobrial, Hamid Asgari, Kerstin Eder

We conduct a case study using YOLOv5 on persons detection to demonstrate our method and usage of the trustworthiness score.

Using Neural Networks for Novelty-based Test Selection to Accelerate Functional Coverage Closure

no code implementations1 Jul 2022 Xuan Zheng, Kerstin Eder, Tim Blackmore

A supervised ML algorithm, as a prevalent option in the previous work, is used to bias the test generation or filter the generated tests.

On Specifying for Trustworthiness

no code implementations22 Jun 2022 Dhaminda B. Abeywickrama, Amel Bennaceur, Greg Chance, Yiannis Demiris, Anastasia Kordoni, Mark Levine, Luke Moffat, Luc Moreau, Mohammad Reza Mousavi, Bashar Nuseibeh, Subramanian Ramamoorthy, Jan Oliver Ringert, James Wilson, Shane Windsor, Kerstin Eder

The main contribution of this article is a set of high-level intellectual challenges for the autonomous systems community related to specifying for trustworthiness.

Hybrid Intelligent Testing in Simulation-Based Verification

no code implementations19 May 2022 Nyasha Masamba, Kerstin Eder, Tim Blackmore

Efficient and effective testing for simulation-based hardware verification is challenging.

Supervised Learning for Coverage-Directed Test Selection in Simulation-Based Verification

no code implementations17 May 2022 Nyasha Masamba, Kerstin Eder, Tim Blackmore

Constrained random test generation is one of the most widely adopted methods for generating stimuli for simulation-based verification.

Operational Adaptation of DNN Classifiers using Elastic Weight Consolidation

1 code implementation30 Apr 2022 Abanoub Ghobrial, Xuan Zheng, Darryl Hond, Hamid Asgari, Kerstin Eder

In this paper, we propose to reduce such threats by investigating how DNN classifiers can adapt their knowledge to learn new information in the AS's operational environment, using only a limited number of observations encountered sequentially during operation.

D-VAL: An automatic functional equivalence validation tool for planning domain models

no code implementations29 Apr 2021 Anas Shrinah, Derek Long, Kerstin Eder

This paper introduces an approach to validate the functional equivalence of planning domain models.

Run-Time Power Modelling in Embedded GPUs with Dynamic Voltage and Frequency Scaling

no code implementations19 Jun 2020 Jose Nunez-Yanez, Kris Nikov, Kerstin Eder, Mohammad Hosseinabady

This paper investigates the application of a robust CPU-based power modelling methodology that performs an automatic search of explanatory events derived from performance counters to embedded GPUs.

Other Computer Science

Goal-constrained Planning Domain Model Verification of Safety Properties

1 code implementation22 Nov 2018 Anas Shrinah, Kerstin Eder

The verification of planning domain models is crucial to ensure the safety, integrity and correctness of planning-based automated systems.

Model-based Test Generation for Robotic Software: Automata versus Belief-Desire-Intention Agents

no code implementations16 Sep 2016 Dejanira Araiza-Illan, Anthony G. Pipe, Kerstin Eder

In this paper, we compare using Belief-Desire-Intention (BDI) agents as models for test generation with more conventional automata-based techniques that exploit model checking, in terms of practicality, performance, transferability to different scenarios, and exploration (`coverage'), through two case studies: a cooperative manufacturing task, and a home care scenario.

Towards the Safety of Human-in-the-Loop Robotics: Challenges and Opportunities for Safety Assurance of Robotic Co-Workers

no code implementations8 Apr 2014 Kerstin Eder, Chris Harper, Ute Leonards

The success of the human-robot co-worker team in a flexible manufacturing environment where robots learn from demonstration heavily relies on the correct and safe operation of the robot.

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