The Inadequacy of Discrete Scenarios in Assessing Deep Neural Networks

The Inadequacy of Discrete Scenarios in Assessing Deep Neural Networks

Many recent approaches for automated driving (AD) functions currently include components relying on deep neural networks (DNNs). One approach in order to test AD functions is the scenario-based approach. This work formalizes and evaluates the parameter discretization process required in order to yie...

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Bibliographic Details
Main Authors: T. Ken Mori, Xu Liang, Lukas Elster, Steven Peters
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Artificial intelligence
autonomous vehicles
concrete scenarios
deep learning
error testing
intelligent vehicles
Online Access:https://ieeexplore.ieee.org/document/9943537/

Internet

https://ieeexplore.ieee.org/document/9943537/

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