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2016 | OriginalPaper | Buchkapitel

Methodology for ADAS Validation: Potential Contribution of Other Scientific Fields Which Have Already Answered the Same Questions

verfasst von: G. Yahiaoui, P. Da Silva Dias

Erschienen in: Energy Consumption and Autonomous Driving

Verlag: Springer International Publishing

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Abstract

Since the 80s, the building of learn and test data bases for learning-based systems (i.e. neural networks) had to cope with problems of picking representative examples and measuring the generalization/the score of the system. And of course, real open world applications cannot be fully tested. It seems that artificial vision-based ADAS now discover the same question, and then, may use the same solutions, involving the same methodology (A.G.E.N.D.A.), using design of experiments and data analysis tools.
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Metadaten
Titel
Methodology for ADAS Validation: Potential Contribution of Other Scientific Fields Which Have Already Answered the Same Questions
verfasst von
G. Yahiaoui
P. Da Silva Dias
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-19818-7_14

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