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Architectural patterns for handling runtime uncertainty of data-driven models in safety-critical perception

Architectural patterns for handling runtime uncertainty of data-driven models in safety-critical perception

Janek Groß
R. Adler
Michael Kläs
Jan Reich
Lisa Jöckel
Roman Gansch
ArXiv (abs)PDFHTML

Papers citing "Architectural patterns for handling runtime uncertainty of data-driven models in safety-critical perception"

4 / 4 papers shown
Title
A Study on Mitigating Hard Boundaries of Decision-Tree-based Uncertainty Estimates for AI Models
A Study on Mitigating Hard Boundaries of Decision-Tree-based Uncertainty Estimates for AI Models
Pascal Gerber
Lisa Jöckel
Michael Kläs
40
4
0
10 Jan 2022
A Comparison of Uncertainty Estimation Approaches in Deep Learning Components for Autonomous Vehicle Applications
A Comparison of Uncertainty Estimation Approaches in Deep Learning Components for Autonomous Vehicle Applications
F. Arnez
H. Espinoza
A. Radermacher
Franccois Terrier
UQCV
42
30
0
26 Jun 2020
Array Programming with NumPy
Array Programming with NumPy
Charles R. Harris
K. Millman
S. Walt
R. Gommers
Pauli Virtanen
...
Tyler Reddy
Warren Weckesser
Hameer Abbasi
C. Gohlke
T. Oliphant
156
14,986
0
18 Jun 2020
On a Formal Model of Safe and Scalable Self-driving Cars
On a Formal Model of Safe and Scalable Self-driving Cars
Shai Shalev-Shwartz
Shaked Shammah
Amnon Shashua
48
740
0
21 Aug 2017

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