Confidence Arguments for Evidence of Performance in Machine Learning for Highly Automated Driving Functions-Reference-Cited by-同舟云学术

Confidence Arguments for Evidence of Performance in Machine Learning for Highly Automated Driving Functions

Published:2019 Issue: Volume: Page:365-377
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Burton Simon,Gauerhof Lydia,Sethy Bibhuti Bhusan,Habli Ibrahim,Hawkins Richard

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-26250-1_30

Reference27 articles.

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3. ISO 26262: Road vehicles - functional safety, second edition. Technical report, International Standards Organisation (ISO), Geneva (2018)

4. SAE J3016: Surface vehicle recommended practice, (r) taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles. Technical report. SAE International, Geneva (2018)

5. Alsallakh, B., Jourabloo, A., Ye, M., Liu, X., Ren, L.: Do convolutional neural networks learn class hierarchy? CoRR arXiv:1710.06501 (2017)

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