Conditional generative adversarial network-based image denoising for defending against adversaria...

[PDF] arxiv.org

Versatile Defense Against Adversarial Attacks on Image Recognition

H Zhang, Z Yao, K Sakurai - arXiv preprint arXiv:2403.08170, 2024 - arxiv.org
Adversarial attacks present a significant security risk to image recognition tasks. Defending
against these attacks in a real-life setting can be compared to the way antivirus software …
被引用次数：3 相关文章 所有 2 个版本

Eliminating adversarial perturbations using image-to-image translation method

H Zhang, Z Yao, K Sakurai - International Conference on Applied …, 2023 - Springer
Convolutional neural networks are widely used for image recognition tasks, but they are
vulnerable to adversarial attacks that can cause the model to misclassify an image. Such …
被引用次数：1 相关文章 所有 4 个版本

Experimental Exploration of the Power of Conditional GAN in Image Reconstruction-Based Adversarial Attack Defense Strategies

H Zhang, K Sakurai - International Conference on Advanced Information …, 2024 - Springer
Adversarial attacks pose a significant threat to the reliability and security of deep learning
models, particularly in image processing applications. Defending against these …
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A Feature Guided Denoising Network For Adversarial Defense

J Li, D Xu, Y Qin, X Deng - 2022 IEEE International Conference …, 2022 - ieeexplore.ieee.org
As neural networks are playing a more and more significant role in many fields, they are also
under the risk of being attacked by adversarial examples, which becomes a great challenge …
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[PDF] ciomp.ac.cn

Global and local feature fusion image dehazing

X Jiang, H Nie, M Zhu - 2023 - ir.ciomp.ac.cn
摘要 Convolution operations with parameter sharing features primarily focus on the
extraction of local features of images but fail to model the features beyond the range of the …
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