ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2304.03973
  4. Cited By
RobCaps: Evaluating the Robustness of Capsule Networks against Affine
  Transformations and Adversarial Attacks

RobCaps: Evaluating the Robustness of Capsule Networks against Affine Transformations and Adversarial Attacks

8 April 2023
Alberto Marchisio
Antonio De Marco
Alessio Colucci
Maurizio Martina
Muhammad Shafique
    AAML
ArXivPDFHTML

Papers citing "RobCaps: Evaluating the Robustness of Capsule Networks against Affine Transformations and Adversarial Attacks"

2 / 2 papers shown
Title
RoHNAS: A Neural Architecture Search Framework with Conjoint
  Optimization for Adversarial Robustness and Hardware Efficiency of
  Convolutional and Capsule Networks
RoHNAS: A Neural Architecture Search Framework with Conjoint Optimization for Adversarial Robustness and Hardware Efficiency of Convolutional and Capsule Networks
Alberto Marchisio
Vojtěch Mrázek
Andrea Massa
Beatrice Bussolino
Maurizio Martina
Muhammad Shafique
AAML
38
5
0
11 Oct 2022
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
287
5,835
0
08 Jul 2016
1