In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to
combat global climate change. We identify two crucial opportunities that AI offers in this …

Automatic medical image segmentation has made great progress owing to powerful deep
representation learning. Inspired by the success of self-attention mechanism in transformer …

Abstract We present Multiscale Vision Transformers (MViT) for video and image recognition,
by connecting the seminal idea of multiscale feature hierarchies with transformer models …

The recently developed vision transformer (ViT) has achieved promising results on image
classification compared to convolutional neural networks. Inspired by this, in this paper, we …

Although convolutional neural network (CNN) paradigms have expanded to transfer
learning and ensemble models from original individual CNN architectures, few studies have …

Deep learning's recent history has been one of achievement: from triumphing over humans
in the game of Go to world-leading performance in image classification, voice recognition …

Abstract We present Mobile Video Networks (MoViNets), a family of computation and
memory efficient video networks that can operate on streaming video for online inference …

Representing features at multiple scales is of great importance for numerous vision tasks.
Recent advances in backbone convolutional neural networks (CNNs) continually …

In natural images, information is conveyed at different frequencies where higher frequencies
are usually encoded with fine details and lower frequencies are usually encoded with global …

Abstract Out-of-distribution (OOD) detection is essential to prevent anomalous inputs from
causing a model to fail during deployment. While improved OOD detection methods have …