This new network is called AdvCapsNet. By considering the risk of adversarial attacks during model design, AVL encourages the Capsule network to focus on the unchanged features within the adversarial inputs, and the model is shown to effectively improve robustness against transfer attacks.
Adversarial Attacks and Defenses in Capsule Networks: A Critical Review of Robustness Challenges and Mitigation Strategies · Benford's law: What does it say on ...
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The review includes an analysis of the adversarial attacks targeting CapsNets, such as manipulating primary capsule votes and direct targeting of CapsNets' ...
The review includes an analysis of the adversarial attacks targeting CapsNets, such as manipulating primary capsule votes and direct targeting of CapsNets' ...
Adversarial Attacks and Defenses in Capsule Networks: A Critical Review of Robustness Challenges and Mitigation Strategies.
At the moment, there are studies aiming at improving the resistance of CapsNets to adversarial attacks [7–9], but these studies focus on CapsNets with dynamic ...
Mar 8, 2023 · This paper aims to provide an in-depth overview of the numerous adversarial attack strategies and defence methods. The theoretical principles, ...
Jun 9, 2019 · This paper extensively evaluates the vulnerability of capsule networks to different adversarial attacks.
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Sep 22, 2023 · AbstractCapsule networks (CapsNets) are new neural networks that classify images based on the spatial relationships of features.
Jun 4, 2019 · This research focused on Capsule Networks vulnerability to adversarial attacks on the German Traffic Sign Recognition Benchmark (GTSRB).
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