VentureBeat

Adversarial attacks in machine learning: What they are and how to stop them

Adversarial machine learning, a technique that attempts to fool models with deceptive data, is a growing threat in the AI and machine learning research community. The most common reason is to cause a ...
ascopubs.org

Using Adversarial Images to Assess the Robustness of Deep Learning Models Trained on Diagnostic Images in Oncology

HealthTree Cure Hub: A Patient-Derived, Patient-Driven Clinical Cancer Information Platform Used to Overcome Hurdles and Accelerate Research in Multiple Myeloma Adversarial images represent a ...
EurekAlert!

An innovative set-level adversarial learning method to improve domain adaptation

Domain adaptation remains a significant challenge in artificial intelligence, especially when models trained in one domain are required to perform well in another.
Forbes

AI Ethics Tempted But Hesitant To Use AI Adversarial Attacks Against The Evils Of Machine Learning, Including For Self-Driving Cars

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. It is widely accepted sage wisdom to garner as much as you can ...
Tech Xplore on MSN

Stress-testing AI vision systems: Rethinking how adversarial images are generated

Deep neural networks (DNNs) have become a cornerstone of modern AI technology, driving a thriving field of research in ...
Mirage News

New Adversarial Learning Boosts Domain Adaptation

Domain adaptation remains a significant challenge in artificial intelligence, especially when models trained in one domain are required to perform ...