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Strategy to Increase the Safety of a DNN-based Perception for HAD
  Systems

Strategy to Increase the Safety of a DNN-based Perception for HAD Systems

20 February 2020
Timo Sämann
Peter Schlicht
Fabian Hüger
ArXivPDFHTML

Papers citing "Strategy to Increase the Safety of a DNN-based Perception for HAD Systems"

4 / 4 papers shown
Title
Online Out-of-Domain Detection for Automated Driving
Online Out-of-Domain Detection for Automated Driving
Timo Sämann
H. Groß
13
0
0
23 Oct 2023
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
251
1,842
0
03 Feb 2017
Safety Verification of Deep Neural Networks
Safety Verification of Deep Neural Networks
Xiaowei Huang
Marta Kwiatkowska
Sen Wang
Min Wu
AAML
183
933
0
21 Oct 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
289
9,167
0
06 Jun 2015
1