Verification of semantic key point detection for aircraft pose estimation
File(s)kr23_boeing.pdf (1.17 MB)
Accepted version
Author(s)
Type
Conference Paper
Abstract
We analyse Semantic Segmentation Neural Networks running on an autonomous aircraft to estimate its pose during landing. We show that automated reasoning techniques from neural network verification can be used to analyse the conditions under which the networks can operate safely, thus providing enhanced assurance guarantees on the behaviour of the over-all pose estimation systems.
Date Issued
2023-09-02
Date Acceptance
2023-05-19
Citation
Proceedings of the 20th International Conference on Principles of Knowledge Representation and Reasoning, 2023, pp.757-762
ISBN
978-1-956792-02-7
ISSN
2334-1033
Publisher
IJCAI Organization
Start Page
757
End Page
762
Journal / Book Title
Proceedings of the 20th International Conference on Principles of Knowledge Representation and Reasoning
Copyright Statement
© 2023 International Joint Conferences on Artificial Intelligence Organization.
Source
The 20th International Conference on Principles of Knowledge Representation and Reasoning (KR2023)
Publication Status
Published
Start Date
2023-09-02
Finish Date
2023-09-08
Coverage Spatial
Rhodes, Greece
Date Publish Online
2023-09-02