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Toward Certification of Machine-Learning Systems for Low Criticality
  Airborne Applications

Toward Certification of Machine-Learning Systems for Low Criticality Airborne Applications

28 September 2022
Konstantin Dmitriev
J. Schumann
F. Holzapfel
ArXivPDFHTML

Papers citing "Toward Certification of Machine-Learning Systems for Low Criticality Airborne Applications"

5 / 5 papers shown
Title
Towards certification: A complete statistical validation pipeline for
  supervised learning in industry
Towards certification: A complete statistical validation pipeline for supervised learning in industry
Lucas Lacasa
Abel Pardo
Pablo Arbelo
Miguel Sánchez
Pablo Yeste
...
Alejandro Martínez-Cava
G. Rubio
Ignacio Gómez
E. Valero
Javier de Vicente
AI4CE
42
1
0
04 Nov 2024
DEM: A Method for Certifying Deep Neural Network Classifier Outputs in
  Aerospace
DEM: A Method for Certifying Deep Neural Network Classifier Outputs in Aerospace
Guy Katz
Natan Levy
Idan Refaeli
Raz Yerushalmi
AAML
18
0
0
04 Jan 2024
AGNES: Abstraction-guided Framework for Deep Neural Networks Security
AGNES: Abstraction-guided Framework for Deep Neural Networks Security
Akshay Dhonthi
Marcello Eiermann
E. M. Hahn
Vahid Hashemi
AAML
24
0
0
07 Nov 2023
Runway Sign Classifier: A DAL C Certifiable Machine Learning System
Runway Sign Classifier: A DAL C Certifiable Machine Learning System
Konstantin Dmitriev
Johann Schumann
Islam Bostanov
Mostafa Abdelhamid
F. Holzapfel
8
3
0
10 Oct 2023
RoMA: a Method for Neural Network Robustness Measurement and Assessment
RoMA: a Method for Neural Network Robustness Measurement and Assessment
Natan Levy
Guy Katz
OOD
AAML
10
13
0
21 Oct 2021
1