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If a Human Can See It, So Should Your System: Reliability Requirements
  for Machine Vision Components

If a Human Can See It, So Should Your System: Reliability Requirements for Machine Vision Components

8 February 2022
Boyue Caroline Hu
Lina Marsso
Krzysztof Czarnecki
Rick Salay
Huakun Shen
Marsha Chechik
ArXivPDFHTML

Papers citing "If a Human Can See It, So Should Your System: Reliability Requirements for Machine Vision Components"

5 / 5 papers shown
Title
Towards Assessing Deep Learning Test Input Generators
Towards Assessing Deep Learning Test Input Generators
Seif Mzoughi
Ahmed Hajyahmed
Mohamed Elshafei
Foutse Khomh anb Diego Elias Costa
D. Costa
AAML
37
0
0
03 Apr 2025
How Mature is Requirements Engineering for AI-based Systems? A
  Systematic Mapping Study on Practices, Challenges, and Future Research
  Directions
How Mature is Requirements Engineering for AI-based Systems? A Systematic Mapping Study on Practices, Challenges, and Future Research Directions
Umm-e- Habiba
Markus Haug
Justus Bogner
Stefan Wagner
24
0
0
11 Sep 2024
Are Transformers More Robust? Towards Exact Robustness Verification for
  Transformers
Are Transformers More Robust? Towards Exact Robustness Verification for Transformers
B. Liao
Chih-Hong Cheng
Hasan Esen
Alois C. Knoll
AAML
26
1
0
08 Feb 2022
RobustBench: a standardized adversarial robustness benchmark
RobustBench: a standardized adversarial robustness benchmark
Francesco Croce
Maksym Andriushchenko
Vikash Sehwag
Edoardo Debenedetti
Nicolas Flammarion
M. Chiang
Prateek Mittal
Matthias Hein
VLM
228
677
0
19 Oct 2020
Safety Verification of Deep Neural Networks
Safety Verification of Deep Neural Networks
Xiaowei Huang
M. Kwiatkowska
Sen Wang
Min Wu
AAML
180
932
0
21 Oct 2016
1