Paper Info
Title
Development Methodologies for Safety Critical Machine Learning Applications in the Automotive Domain: A Survey
Abstract
Enabled by recent advances in the field of machine learning, the automotive industry pushes towards automated driving. The development of traditional safety-critical automotive software is subject to rigorous processes, ensuring its dependability while decreasing the probability of failures. However, the development and training of machine learning applications substantially differs from tradition...
Year
DOI
Venue
2021
10.1109/CVPRW53098.2021.00023
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Keywords
DocType
ISSN
Training,Systematics,Machine learning,Tools,Network architecture,Data models,Software
Conference
2160-7508
ISBN
Citations 
PageRank 
978-1-6654-4899-4
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Martin Rabe100.34
Stefan Milz2177.74
Patrick Mäder349236.96