Some of the biological knowledge obtained from fundamental research will be implemented
in applied plant breeding. To bridge basic research and breeding practice, machine learning …

Condition monitoring plays a vital role in ensuring the reliability and optimal performance of
various engineering systems. Traditional methods for condition monitoring rely on physics …

Deep generative models are becoming increasingly powerful, now generating diverse high
fidelity photo-realistic samples given text prompts. Have they reached the point where …

Massive web datasets play a key role in the success of large vision-language models like
CLIP and Flamingo. However, the raw web data is noisy, and existing filtering methods to …

Human-centricity is the core value behind the evolution of manufacturing towards Industry
5.0. Nevertheless, there is a lack of architecture that considers safety, trustworthiness, and …

The recent advance in vision-language models is largely attributed to the abundance of
image-text data. We aim to replicate this success for video-language models but there …

Many computer vision techniques infer properties of our physical world from images.
Although images are formed through the physics of light and mechanics, computer vision …

In this work, we present a method for RGB-based action recognition using multi-view videos.
We present a supervised contrastive learning framework to learn a feature embedding …

Deep neural networks (DNNs) have become powerful and increasingly ubiquitous tools to
model human cognition, and often produce similar behaviors. For example, with their …

To interpret our surroundings, the brain uses a visual categorization process. Current
theories and models suggest that this process comprises a hierarchy of different …