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.

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 ...

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 ...

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 ...

This is an example of data poisoning, a special type of adversarial attack, a series of techniques that target the behavior of machine learning and deep learning models. If applied successfully ...

The angle and placement of the patch made a difference to the AI’s ability to detect a person There is growing interest in real world adversarial attacks – which are ideally both physically ...

However, the researchers believe their new findings show that adversarial examples make AI “vulnerable” and actually do pose a “practical concern”. As well as tricking InceptionV3 into ...

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 ...

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.

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. The team at the Univ… ...