Analytics

Enterprise Analytics

Making Machine Learning Transparent ML research field has a frequent lack of connection between ML research and real-world impact because of complexity of ML models. For instance, for a domain expert who may not have expertise in ML or programming, an ML algorithm is as a “black-box”, where the user […] Read more… Multimodal Cognitive […]

Cognitive load (CL) refers to the amount of mental demand imposed on a user by a particular task, and has been associated with the limited capacity of working memory and the ability to process novel information. High levels of CL are known to decrease effectiveness and performance of users, as well as their ability to […]

Data61 provides decision support for owners and maintainers of civil and industrial assets. Sensing, continuous monitoring and advanced data analysis techniques enable asset managers to make more informed maintenance decisions. The Challenge Assets are typically maintained when something goes wrong or according to preventative maintenance schedules. These approaches do not make the best use of […]

Trust has been realised as one of the most important factors in management and organisational behaviour for all personal and business decision making as well as for efficiency and task performance. It is also found to be a critical factor driving human behaviour in human-machine interactions with automation systems in modern complex high-risk domains such […]

Deep learning for computer vision aims at learning image presentations from large collections of visual data. Leveraged by the powerful Graphical Processing Unit (GPU), deep learning has become one of the fastest advancing field in computer vision, and outperform many traditional techniques in a number of benchmark datasets in multiple areas. Our colleagues have successfully […]

The Riemannian Geometry Team (RGT) pursues fundamental research based on the notion of Riemannian geometry to achieve accurate and discriminative models for visual information. RGT has investigated several central research questions in vision and developed efficient solutions for them. Examples are: Kernel methods on Riemannian manifolds: Kernel methods in Euclidean spaces have shown to be […]

We aim to automatically detect forest cover change based on analysing large scale satellite imagery datasets. Our approach exploits recent success of computer vision algorithms on change detection and spatio-temporal feature learning. Problem setting: Satellite images provide a rich source of information for monitoring changes in forest vegetation, which is fundamental to assessing impacts of […]

This database addresses the need for experimental data to quantitatively evaluate emerging road detection and photometric invariant algorithms. These images were captured using an on-board camera mounted on the windshield of a moving vehicle. The main challenge is dealing with lighting variations and shadows. The database consists (right now) of two sequences acquired on the […]