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Benchmarking Robustness of Deep Learning Classifiers Using Two-Factor
  Perturbation

Benchmarking Robustness of Deep Learning Classifiers Using Two-Factor Perturbation

2 March 2022
Wei Dai
Daniel Berleant
    VLM
    AAML
ArXivPDFHTML

Papers citing "Benchmarking Robustness of Deep Learning Classifiers Using Two-Factor Perturbation"

5 / 5 papers shown
Title
P-TimeSync: A Precise Time Synchronization Simulation with Network
  Propagation Delays
P-TimeSync: A Precise Time Synchronization Simulation with Network Propagation Delays
Wei Dai
Rui Zhang
Jinwei Liu
33
0
0
02 Jan 2024
ASI: Accuracy-Stability Index for Evaluating Deep Learning Models
ASI: Accuracy-Stability Index for Evaluating Deep Learning Models
Wei Dai
Daniel Berleant
4
0
0
26 Nov 2023
Investigating the Corruption Robustness of Image Classifiers with Random
  Lp-norm Corruptions
Investigating the Corruption Robustness of Image Classifiers with Random Lp-norm Corruptions
George J. Siedel
Weijia Shao
S. Vock
Andrey Morozov
17
1
0
09 May 2023
Discovering Limitations of Image Quality Assessments with Noised Deep
  Learning Image Sets
Discovering Limitations of Image Quality Assessments with Noised Deep Learning Image Sets
Wei Dai
Daniel Berleant
11
3
0
19 Oct 2022
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
293
3,110
0
04 Nov 2016
1