Runtime Monitoring of Accidents in Driving Recordings with Multi-type Logic in Empirical Models-Reference-Cited by-同舟云学术

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Runtime Monitoring of Accidents in Driving Recordings with Multi-type Logic in Empirical Models

Published:2023 Issue: Volume: Page:376-388
ISSN:0302-9743
Container-title:Runtime Verification
language:
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Author:

An Ziyan^ORCID,Wang Xia^ORCID,T. Johnson Taylor^ORCID,Sprinkle Jonathan^ORCID,Ma Meiyi^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-44267-4_21

Reference34 articles.

1. Bakar, A., Rahman, T., Shafik, R., Kawsar, F., Montanari, A.: Adaptive intelligence for batteryless sensors using software-accelerated tsetlin machines. In: Proceedings of SenSys (2022)

2. Lecture Notes in Computer Science;A Balakrishnan,2021

3. Balakrishnan, A., et al.: Specifying and evaluating quality metrics for vision-based perception systems. In: 2019 Design, Automation & Test in Europe Conference & Exhibition (DATE), pp. 1433–1438. IEEE (2019)

4. Bashetty, S.K., Amor, H.B., Fainekos, G.: Deepcrashtest: turning dashcam videos into virtual crash tests for automated driving systems. In: 2020 IEEE International Conference on Robotics and Automation (ICRA), pp. 11353–11360. IEEE (2020)

5. Breiman, L.: Random forests. Mach. Learn. 45, 5–32 (2001)

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