EVALUATING THE IMPACT OF UNCERTAINTY ON THE INTEGRITY OF DEEP NEURAL NETWORKS

EVALUATING THE IMPACT OF UNCERTAINTY ON THE INTEGRITY OF DEEP NEURAL NETWORKS

Deep Neural Networks (DNNs) have proven excellent performance and are very successful in image classification and object detection. Safety critical industries such as the automotive and aerospace industry aim to develop autonomous vehicles with the help of DNNs. In order to certify the usage of DNNs...

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Bibliographic Details
Main Author: Harborn, Jakob
Format: Others
Language:English
Published: Mälardalens högskola, Akademin för innovation, design och teknik 2021
Subjects:
Uncertainty
Deep Neural Network
Bayesian Neural Network
Dependability
Integrity
Probability
Computer Vision and Robotics (Autonomous Systems)
Datorseende och robotik (autonoma system)
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-53395

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-53395

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