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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Noise is Inside Me! Generating Adversarial Perturbations with Noise Derived from Natural Filters
Akshay Agarwal, Mayank Vatsa, Richa Singh, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (2020), pp. 3354-3363
Closed Access | Times Cited: 24

Showing 24 citing articles:

Recognition-Oriented Image Compressive Sensing With Deep Learning
Siwang Zhou, Xiaoning Deng, Chengqing Li, et al.
IEEE Transactions on Multimedia (2022) Vol. 25, pp. 2022-2032
Closed Access | Times Cited: 52
Image Transformation based Defense Against Adversarial Perturbation on Deep Learning Models
Akshay Agarwal, Richa Singh, Mayank Vatsa, et al.
IEEE Transactions on Dependable and Secure Computing (2020), pp. 1-1
Closed Access | Times Cited: 46
Cross-Domain Adversarial Attacks and Robust Defense Mechanisms for Multimodal Neural Networks
Jay Barach
Communications in computer and information science (2025), pp. 345-362
Closed Access
DAMAD: Database, Attack, and Model Agnostic Adversarial Perturbation Detector
Akshay Agarwal, Gaurav Goswami, Mayank Vatsa, et al.
IEEE Transactions on Neural Networks and Learning Systems (2021) Vol. 33, Iss. 8, pp. 3277-3289
Closed Access | Times Cited: 15
Crafting Adversarial Perturbations via Transformed Image Component Swapping
Akshay Agarwal, Nalini Ratha, Mayank Vatsa, et al.
IEEE Transactions on Image Processing (2022) Vol. 31, pp. 7338-7349
Closed Access | Times Cited: 9
Corruption depth: Analysis of DNN depth for misclassification
Akshay Agarwal, Mayank Vatsa, Richa Singh, et al.
Neural Networks (2023) Vol. 172, pp. 106013-106013
Closed Access | Times Cited: 5
Benchmarking Robustness Beyond $$l_p$$ Norm Adversaries
Akshay Agarwal, Nalini Ratha, Mayank Vatsa, et al.
Lecture notes in computer science (2023), pp. 342-359
Closed Access | Times Cited: 4
A Survey of Robustness and Safety of 2D and 3D Deep Learning Models against Adversarial Attacks
Yanjie Li, Bin Xie, Songtao Guo, et al.
ACM Computing Surveys (2023) Vol. 56, Iss. 6, pp. 1-37
Open Access | Times Cited: 4
ARES: On Adversarial Robustness Enhancement for Image Steganographic Cost Learning
Qi Cui, Zhili Zhou, Ruohan Meng, et al.
IEEE Transactions on Multimedia (2024) Vol. 26, pp. 6542-6553
Closed Access | Times Cited: 1
The Unseen Adversaries: Robust and Generalized Defense Against Adversarial Patches
Vishesh Kumar, Akshay Agarwal
(2024)
Closed Access | Times Cited: 1
WaveTransform: Crafting Adversarial Examples via Input Decomposition
Divyam Anshumaan, Akshay Agarwal, Mayank Vatsa, et al.
Lecture notes in computer science (2020), pp. 152-168
Closed Access | Times Cited: 9
Offloading Deep Learning Empowered Image Segmentation from UAV to Edge Server
Huseyin Enes Ilhan, Sedat Özer, Güneş Karabulut Kurt, et al.
(2021), pp. 296-300
Closed Access | Times Cited: 9
[Retracted] Adversarial Attacks Defense Method Based on Multiple Filtering and Image Rotation
Feng Li, Xuehui Du, Liu Zhang
Discrete Dynamics in Nature and Society (2022) Vol. 2022, Iss. 1
Open Access | Times Cited: 5
Intelligent and Adaptive Mixup Technique for Adversarial Robustness
Akshay Agarwal, Mayank Vatsa, Richa Singh, et al.
2022 IEEE International Conference on Image Processing (ICIP) (2021), pp. 824-828
Closed Access | Times Cited: 7
Is large improvement in efficiency of impulsive noise removal in color images still possible?
Łukasz Maliński, Krystian Radlak, Bogdan Smołka
PLoS ONE (2021) Vol. 16, Iss. 6, pp. e0253117-e0253117
Open Access | Times Cited: 6
Benchmarking Image Classifiers for Physical Out-of-Distribution Examples Detection
Ojaswee, Akshay Agarwal, Nalini Ratha
(2023), pp. 4429-4437
Closed Access | Times Cited: 2
Attack Agnostic Adversarial Defense via Visual Imperceptible Bound
Saheb Chhabra, Akshay Agarwal, Richa Singh, et al.
2022 26th International Conference on Pattern Recognition (ICPR) (2021) Vol. 2, pp. 5302-5309
Open Access | Times Cited: 5
Privacy-Preserving Link Scheduling for Wireless Networks
Maryam Abbasalizadeh, Jeffrey Chan, Pranathi Rayavaram, et al.
IEEE Access (2024) Vol. 12, pp. 109657-109672
Open Access
Discerning the Chaos: Detecting Adversarial Perturbations while Disentangling Intentional from Unintentional Noises
Anubhooti Jain, S. N. Roy, Kamini Gupta, et al.
(2024), pp. 1-10
Open Access
Restoring Noisy Images Using Dual-Tail Encoder-Decoder Signal Separation Network
Akshay Agarwal, Mayank Vatsa, Richa Singh, et al.
Lecture notes in computer science (2024), pp. 329-345
Closed Access
Role of Optimizer on Network Fine-tuning for Adversarial Robustness (Student Abstract)
Akshay Agarwal, Mayank Vatsa, Richa Singh
Proceedings of the AAAI Conference on Artificial Intelligence (2021) Vol. 35, Iss. 18, pp. 15745-15746
Open Access | Times Cited: 1
Robustness Against Gradient based Attacks through Cost Effective Network Fine-Tuning
Akshay Agarwal, Nalini Ratha, Richa Singh, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (2023), pp. 28-37
Closed Access
Attention Guided Multi-attribute Architecture For Deepfake Detection
Rohan Sharma, Bhavin Jawade, Akshay Agarwal, et al.
(2023), pp. 1-4
Closed Access
WaveTransform: Crafting Adversarial Examples via Input Decomposition
Divyam Anshumaan, Akshay Agarwal, Mayank Vatsa, et al.
arXiv (Cornell University) (2020)
Closed Access
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