LUMISTAR concluded its debut at CES 2026 with overwhelming attention from attendees, media, and industry professionals, as ...

McGill University researchers found training your brain in a specific, targeted, computerized way can produce important ...

X-ray tomography is a powerful tool that enables scientists and engineers to peer inside of objects in 3D, including computer ...

Abstract: Deep learning models in computer vision face challenges such as high computational resource demands and limited generalization in practical scenarios. To address these issues, this study ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Meta AI glasses combine advanced computer vision, voice AI, and an innovative in-lens display with neural band control, transforming how users see, hear, and interact with the world. Ray-Ban - ...

Computer vision moved fast in 2025: new multimodal backbones, larger open datasets, and tighter model–systems integration. Practitioners need sources that publish rigorously, link code and benchmarks, ...

DINOv3 represents a major leap in computer vision: its frozen universal backbone and SSL approach enable researchers and developers to tackle annotation-scarce tasks, deploy high-performance models ...

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.

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 ...

New research demonstartes the power of combining computer vision with generative models to address key inefficiencies in smart farming. Published in Applied Sciences, the study emphasizes how these AI ...