Deep Learning is the most widely used tool in the contemporary field of computer vision. Its
ability to accurately solve complex problems is employed in vision research to learn deep …

This work provides the community with a timely comprehensive review of backdoor attacks
and countermeasures on deep learning. According to the attacker's capability and affected …

Deep learning is at the heart of the current rise of artificial intelligence. In the field of
computer vision, it has become the workhorse for applications ranging from self-driving cars …

We consider the zeroth-order optimization problem in the huge-scale setting, where the
dimension of the problem is so large that performing even basic vector operations on the …

Adversarial attacks have been demonstrated to fool the deep classification networks. There
are two key characteristics of these attacks: firstly, these perturbations are mostly additive …

With a limited query budget and only the final decision of a target model, how to find
adversarial examples with low-magnitude distortion has attracted great attention among …

Deep neural networks (DNNs) are shown to be vulnerable to universal adversarial
perturbations (UAP), a single quasi-imperceptible perturbation that deceives the DNNs on …

For smart manufacturing systems, quality monitoring of welding has already started to shift
from empirical modeling to knowledge integration directly from the captured data by utilizing …

Although recent deep neural network algorithm has shown tremendous success in several
computer vision tasks, their vulnerability against minute adversarial perturbations has raised …

Image hiding is the process of hiding a secret image in another meaningful image or other
carriers so that the secret image remains imperceptible and can be recovered securely at …