For humans, identifying items in a scene — whether that’s an avocado or an Aventador, a pile of mashed potatoes or an alien mothership — is as simple as looking at them. But for artificial ...

For people, matching what they see on the ground to a map is second nature. For computers, it has been a major challenge. A Cornell research team has introduced a new method that helps machines make ...

Computer vision (CV) and image processing are two closely related fields that utilize techniques from artificial intelligence (AI) and pattern recognition to derive meaningful information from images, ...

Vision Transformers, or ViTs, are a groundbreaking learning model designed for tasks in computer vision, particularly image recognition. Unlike CNNs, which use convolutions for image processing, ViTs ...

Two years ago, Microsoft announced Florence, an AI system that it pitched as a “complete rethinking” of modern computer vision models. Unlike most vision models at the time, Florence was both “unified ...

Christoph Wagner is the CEO of Scanbot SDK, a software development company specializing in data capture software for mobile and web apps. Recent leaps in generative AI have demonstrated the disruptive ...

What if you could teach a computer to recognize a zebra without ever showing it one? Imagine a world where object detection isn’t bound by the limits of endless training data or high-powered hardware.

Continuing on its open source tear, Meta today released a new AI benchmark, FACET, designed to evaluate the “fairness” of AI models that classify and detect things in photos and videos, including ...