The self-attention-based transformer model was first introduced by Vaswani et al. in their paper Attention Is All You Need in 2017 and has been widely used in natural language processing. A ...

In the last decade, convolutional neural networks (CNNs) have been the go-to architecture in computer vision, owing to their powerful capability in learning representations from images/videos.

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. In this episode, Thomas Betts chats with ...

Meta AI Research open-sourced DINOv2, a foundation model for computer vision (CV) tasks. DINOv2 is pretrained on a curated dataset of 142M images and can be used as a backbone for several tasks, ...

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 ...

An autonomous vehicle must rapidly and accurately recognize objects that it encounters, from an idling delivery truck parked at the corner to a cyclist whizzing toward an approaching intersection. To ...

This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. (In partnership with Paperspace) In recent years, the transformer model has ...