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David and Goliath: An Empirical Evaluation of Attacks and Defenses for
  QNNs at the Deep Edge

David and Goliath: An Empirical Evaluation of Attacks and Defenses for QNNs at the Deep Edge

8 April 2024
Miguel Costa
Sandro Pinto
    AAML
ArXivPDFHTML

Papers citing "David and Goliath: An Empirical Evaluation of Attacks and Defenses for QNNs at the Deep Edge"

3 / 3 papers shown
Title
Shifting Capsule Networks from the Cloud to the Deep Edge
Shifting Capsule Networks from the Cloud to the Deep Edge
Miguel Costa
Diogo Costa
T. Gomes
Sandro Pinto
21
5
0
06 Oct 2021
On the Adversarial Robustness of Quantized Neural Networks
On the Adversarial Robustness of Quantized Neural Networks
Micah Gorsline
James T. Smith
Cory E. Merkel
AAML
54
18
0
01 May 2021
Benchmarking TinyML Systems: Challenges and Direction
Benchmarking TinyML Systems: Challenges and Direction
Colby R. Banbury
Vijay Janapa Reddi
Max Lam
William Fu
A. Fazel
...
Jae-sun Seo
Jeff Sieracki
Urmish Thakker
Marian Verhelst
Poonam Yadav
109
228
0
10 Mar 2020
1