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Closeness and Uncertainty Aware Adversarial Examples Detection in
  Adversarial Machine Learning
v1v2 (latest)

Closeness and Uncertainty Aware Adversarial Examples Detection in Adversarial Machine Learning

Computers & electrical engineering (CEE), 2020
11 December 2020
Ömer Faruk Tuna
Ferhat Ozgur Catak
M. T. Eskil
    AAML
ArXiv (abs)PDFHTML

Papers citing "Closeness and Uncertainty Aware Adversarial Examples Detection in Adversarial Machine Learning"

8 / 8 papers shown
Adversarial Examples in Environment Perception for Automated Driving (Review)
Adversarial Examples in Environment Perception for Automated Driving (Review)
Jun Yan
Huilin Yin
AAML
370
1
0
11 Apr 2025
Adversarial Challenges in Network Intrusion Detection Systems: Research
  Insights and Future Prospects
Adversarial Challenges in Network Intrusion Detection Systems: Research Insights and Future ProspectsIEEE Access (IEEE Access), 2024
Sabrine Ennaji
Fabio De Gaspari
Dorjan Hitaj
Alicia Kbidi
Luigi V. Mancini
AAML
587
32
0
27 Sep 2024
SoK: Analyzing Adversarial Examples: A Framework to Study Adversary
  Knowledge
SoK: Analyzing Adversarial Examples: A Framework to Study Adversary Knowledge
L. Fenaux
Florian Kerschbaum
AAML
382
0
0
22 Feb 2024
ScatterUQ: Interactive Uncertainty Visualizations for Multiclass Deep
  Learning Problems
ScatterUQ: Interactive Uncertainty Visualizations for Multiclass Deep Learning ProblemsVisual .. (VISUAL), 2023
Harry Li
Steven Jorgensen
J. Holodnak
Allan B. Wollaber
OODUQCV
221
5
0
08 Aug 2023
Uncertainty Aware Deep Learning Model for Secure and Trustworthy Channel
  Estimation in 5G Networks
Uncertainty Aware Deep Learning Model for Secure and Trustworthy Channel Estimation in 5G NetworksMediterranean Conference on Embedded Computing (MECO), 2023
Ferhat Ozgur Catak
Marc Brittain
Murat Kuzlu
Christine Serres
UQCV
149
2
0
04 May 2023
Unreasonable Effectiveness of Last Hidden Layer Activations for
  Adversarial Robustness
Unreasonable Effectiveness of Last Hidden Layer Activations for Adversarial RobustnessAnnual International Computer Software and Applications Conference (COMPSAC), 2022
Ömer Faruk Tuna
Ferhat Ozgur Catak
M. T. Eskil
AAML
260
5
0
15 Feb 2022
Prediction Surface Uncertainty Quantification in Object Detection Models
  for Autonomous Driving
Prediction Surface Uncertainty Quantification in Object Detection Models for Autonomous Driving
Ferhat Ozgur Catak
T. Yue
Shaukat Ali
165
27
0
11 Jul 2021
Exploiting epistemic uncertainty of the deep learning models to generate
  adversarial samples
Exploiting epistemic uncertainty of the deep learning models to generate adversarial samplesMultimedia tools and applications (MTA), 2021
Ömer Faruk Tuna
Ferhat Ozgur Catak
M. T. Eskil
AAML
287
34
0
08 Feb 2021
1
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