The ability to predict, anticipate and reason about future outcomes is a key component of
intelligent decision-making systems. In light of the success of deep learning in computer …

Development of computer vision algorithms using convolutional neural networks and deep
learning has necessitated ever greater amounts of annotated and labelled data to produce …

On-orbit proximity operations in space rendezvous, docking and debris removal require
precise and robust 6D pose estimation under a wide range of lighting conditions and against …

Recent research in embodied AI has been boosted by the use of simulation environments to
develop and train robot learning approaches. However, the use of simulation has skewed …

The recognition of human actions based on artificial intelligence methods to enable Human–
Robot Collaboration (HRC) inside working environments remains a challenge, especially …

Existing work on VQA explores data augmentation to achieve better generalization by
perturbing the images in the dataset or modifying the existing questions and answers. While …

Artificial intelligence (AI) has emerged as a fundamental component of global agricultural
research that is poised to impact on many aspects of plant science. In digital phenomics, AI …

To train deep learning models for vision-based action recognition of elders' daily activities,
we need large-scale activity datasets acquired under various daily living environments and …

This paper presents an updated and broad review of swarm robotics research papers
regarding software, hardware, simulators and applications. The evolution from its concept to …

With the exponential growth of new technology, it is timely that social psychologists continue
to develop new and effective solutions to old but existing problems, including prejudice. One …