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Study mode:
on
1
Intro
2
Motivation
3
Contributions
4
Watermarking Definition
5
Watermarking Taxonomy
6
Attack Taxonomy
7
Decision Threshold
8
Nash Equilibrium
9
Setup
10
Runtime Analysis
11
Fidelity after Embedding
12
Single Scheme vs All Attacks
13
Discussion
14
Guidelines
15
Conclusion
Description:
Explore the robustness of image classification deep neural network watermarking in this 17-minute IEEE conference talk. Delve into the motivations, contributions, and key concepts surrounding watermarking techniques for neural networks. Examine the watermarking taxonomy, attack taxonomy, decision threshold, and Nash equilibrium. Analyze the setup, runtime, and fidelity after embedding, comparing single schemes against all attacks. Gain valuable insights into guidelines and conclusions drawn from this systematic study on the effectiveness of deep neural network watermarking methods.

How Robust Is Image Classification Deep Neural Network Watermarking?

IEEE
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