Neuroscientists have been trying to understand how the brain processes visual information for over a century. The development ...

For artificial intelligence to realize its potential — to relieve humans from mundane tasks, make life easier, and eventually invent entirely new solutions to our problems — computers will need to ...

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 ...

Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines are ...

Vision-and-Language Navigation (VLN) is a dynamic interdisciplinary field at the interface of computer vision, natural language processing and robotics. It involves the design of autonomous agents ...

Vision language models (VLMs) have made impressive strides over the past year, but can they handle real-world enterprise challenges? All signs point to yes, with one caveat: They still need maturing ...

The Computer Vision and Machine Learning focus area builds on the pioneering work at UB in enabling AI innovation in language and vision analytic sub-systems and their application to the fields of ...