Adversarial Robustness of Vision Transformers Versus Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Adversarial Robustness of Vision Transformers Versus Convolutional Neural Networks

Published:2024 Issue: Volume:12 Page:105281-105293
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Ali Kazim¹,Bhatti Muhammad Shahid²^ORCID,Saeed Atif²^ORCID,Athar Atifa²^ORCID,Al Ghamdi Mohammed A.³^ORCID,Almotiri Sultan H.⁴^ORCID,Akram Samina⁵

Affiliation:

1. Punjab Education Department, Government of Punjab, Layyah, Pakistan

2. Department of Computer Science, COMSATS University Islamabad, Lahore Campus, Lahore, Pakistan

3. Department of Computer Science and Artificial Intelligence, College of Computing, Umm Al-Qura University, Makkah, Saudi Arabia

4. Department of Cybersecurity, College of Computing, Umm Al-Qura University, Makkah, Saudi Arabia

5. Department of Computer Science, Faculty of Information Technology, University of Central Punjab, Lahore, Pakistan

Funder

Deputyship for Research and Innovation, Ministry of Education, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10614176.pdf?arnumber=10614176

Reference56 articles.

1. BERT: Pre-training of deep bidirectional transformers for language understanding;Devlin;arXiv:1810.04805,2018

2. XLNet: Generalized autoregressive pretraining for language understanding;Yang

3. ERNIE: Enhanced representation through knowledge integration;Sun;arXiv:1904.09223,2019

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