Many commercial image cropping models utilize saliency maps (also known as gaze estimation) to identify the most critical areas within an image. In this study, researchers developed innovative ...

Recent years have seen the wide application of NLP models in crucial areas such as finance, medical treatment, and news media, raising concerns about the model robustness. Existing methods are mainly ...

Machine learning, for all its benevolent potential to detect cancers and create collision-proof self-driving cars, also threatens to upend our notions of what's visible and hidden. It can, for ...

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 ...

Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here. No matter the claimed robustness of AI and machine ...

Adversarial attacks are an increasingly worrisome threat to the performance of artificial intelligence applications. If an attacker can introduce nearly invisible alterations to image, video, speech, ...

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing, ...

The algorithms that computers use to determine what objects are–a cat, a dog, or a toaster, for instance–have a vulnerability. This vulnerability is called an adversarial example. It’s an image or ...