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, ...

Computer vision trains AI to interpret images, automating tasks like driving and product tracking. Applications include Amazon's "Just Walk Out" tech and autonomous vehicles' navigation systems. Uses ...

The global computer vision in healthcare market is projected to expand at a compound annual growth rate (CAGR) of approximately 25% over the forecast period. This robust growth is driven by the ...

A Cornell research team has introduced a new method that helps machines make these connections—an advance that could improve ...

Vision systems are rapidly becoming ubiquitous, driven by big improvements in image sensors as well as new types of sensors. While the sensor itself often is developed using mature-node silicon, ...

We design, model, and build systems that combine sensors, displays, and novel optical elements to enable new functionality in cameras and displays for applications in medical, astronomical, and ...

Computer vision in healthcare is making disease detection much earlier and more accurate, especially with things like cancer, by spotting tiny details in scans. During surgery, this tech helps ...

Computer Vision Syndrome (CVS) and Digital Eye Strain describe a cluster of ocular and extraocular symptoms that arise from prolonged exposure to digital screens. This condition encompasses symptoms ...

When artificial intelligence (AI) hits the headlines, it’s usually bad news pertaining to the perils of face recognition. It was only recently that Twitter had to remove an AI-based cropping tool due ...

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 ...