Crafting Adversarial Perturbations via Transformed Image Component Swapping-Reference-Cited by-同舟云学术

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Crafting Adversarial Perturbations via Transformed Image Component Swapping

Published:2022 Issue: Volume:31 Page:7338-7349
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Agarwal Akshay¹^ORCID,Ratha Nalini²^ORCID,Vatsa Mayank³^ORCID,Singh Richa³^ORCID

Affiliation:

1. Department of Data Science and Engineering, IISER Bhopal, Bhauri, Madhya Pradesh, India

2. Department of Computer Science and Electrical Engineering, University at Buffalo, Buffalo, NY, USA

3. Department of Computer Science Engineering, IIT Jodhpur, Jodhpur, India

Funder

Swarnajayanti Fellowship by the Government of India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9626658/09887823.pdf?arnumber=9887823

Reference59 articles.

1. Adversarial machine learning in image classification: A survey towards the Defender’s perspective;machado;arXiv 2009 03728,2020

2. Learning Transferable Adversarial Examples via Ghost Networks

3. Geometric Robustness of Deep Networks: Analysis and Improvement

4. Research Progress and Challenges on Application-Driven Adversarial Examples: A Survey

5. Dropping Pixels for Adversarial Robustness

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2. Exploring Adversarial Robustness of Vision Transformers in the Spectral Perspective;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03

3. Exploring Imperceptible Adversarial Examples in $$YC_bC_r$$ Color Space;Lecture Notes in Computer Science;2024

4. Benchmarking Image Classifiers for Physical Out-of-Distribution Examples Detection;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02

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