Reuse, remanufacturing and recycling in the steel sector.

The global steel sector is undergoing a transition from being a major CO emitter to a more sustainable circular material service provider, moving towards (near) net zero CO through combined strategies of reuse, remanufacturing, recycling and changes to primary steelmaking. This paper considers the transition using the UK as an example, based on the current sector state and future plans/opportunities. Some key enablers/barriers have been identified, and case studies are presented on the current state of knowledge and technology developments.

Virtual Category Learning: A Semi-Supervised Learning Method for Dense Prediction With Extremely Limited Labels.

Due to the costliness of labelled data in real-world applications, semi-supervised learning, underpinned by pseudo labelling, is an appealing solution. However, handling confusing samples is nontrivial: discarding valuable confusing samples would compromise the model generalisation while using them for training would exacerbate the issue of confirmation bias caused by the resulting inevitable mislabelling. To solve this problem, this paper proposes to use confusing samples proactively without label correction.

Semi-Supervised Unpaired Medical Image Segmentation Through Task-Affinity Consistency.

Deep learning-based semi-supervised learning (SSL) algorithms are promising in reducing the cost of manual annotation of clinicians by using unlabelled data, when developing medical image segmentation tools. However, to date, most existing semi-supervised learning (SSL) algorithms treat the labelled images and unlabelled images separately and ignore the explicit connection between them; this disregards essential shared information and thus hinders further performance improvements. To mine the shared information between the labelled and unlabelled images, we introduce a class-specific representation extraction approach, in which a task-affinity module is specifically designed for representation extraction.

Using virtual environments to facilitate refugee integration in third countries.

Virtual experiences (VEs) have significant potential to enrich emotional interactions, to encourage socialisation and improve communication. In education, VEs offer new approaches for delivering content. In this paper we consider the application of VEs for assisting refugees in Senegal to learn how to navigate the complexities of the UK health system; a substantial stumbling block for their integration into society and for their own health.

Deep Synthesis of Cloud Lighting.

Current appearance models for the sky are able to represent clear-sky illumination to a high degree of accuracy. However, these models all lack a common feature of real skies: clouds. These are an essential component for many applications which rely on realistic skies, such as image editing and synthesis.