Adversarial patches represent a critical form of physical adversarial attacks, posing significant risks to the security of neural network-based object detection systems. Previous research on ...

For example, place a patch designed to look like a computer next to a banana and the algorithm will see a toaster. Put it next to a dog and the algorithm will see a toaster. You get the idea.

No, it’s not a deleted Q gadget from some late-stage Pierce Brosnan 007 movie. Researchers really have created a patch that could effectively disguise aerial vehicles from A.I. image recognition ...

Deep neural networks (DNNs) have been widely used in remote sensing but demonstrated to be sensitive with adversarial examples. By introducing carefully designed perturbations to clean images, DNNs ...

A research team at the University of Adelaide in Australia has announced a new attack method called Universal NaTuralistic adversarial paTches (TnT) against neural networks for face recognition ...

Seminar by Devon Zhangcontext of Connected and Automated Vehicles (CAVs), presenting a comprehensive study on the vulnerabilities and defense mechanisms against adversarial attacks in two critical ...

It's not the only adversarial patch of its kind. Dutch artist and designer Simone C. Niquille created a series of t-shirts that are covered in a bunch of bizarre faces that are able to confuse ...

Adversarial attacks are not something new to the world of Deep Networks used for image recognition. However, as the research with Deep Learning grows, more flaws are uncovered.