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 ...

Transformers, first proposed in a Google research paper in 2017, were initially designed for natural language processing (NLP) tasks. Recently, researchers applied transformers to vision applications ...

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 ...

The increase in skin conditions, especially skin cancers, shows the need for accurate diagnostics. Traditional imaging methods struggle to capture complex skin lesion patterns, leading to potential ...

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 ...