Videnskabsdiplomati i Arktis – et udenrigspolitisk værktøj

Temaet afsluttes med de tre vinderartikler fra Det Udenrigspolitiske Selskabs og Udenrigs- ministeriets artikelkonkurrence, der netop havde Arktis som emne

Dynamics are Important for the Recognition of Equine Pain in Video

A prerequisite to successfully alleviate pain in animals is to recognize it, which is a great challenge in non-verbal species. Furthermore, prey animals such as horses tend to hide their pain. In this study, we propose a deep recurrent two-stream architecture for the task of distinguishing pain from non-pain in videos of horses. Different models are evaluated on a unique dataset showing horses under controlled trials with moderate pain induction, which has been presented in earlier work. Sequential models are experimentally compared to single-frame models, showing the importance of the temporal dimension of the data, and are benchmarked against a veterinary expert classification of the data. We additionally perform baseline comparisons with generalized versions of state-of-the-art human pain recognition methods. While equine pain detection in machine learning is a novel field, our results surpass veterinary expert performance and outperform pain detection results reported for other larger non-human species.Comment: CVPR 2019: IEEE Conference on Computer Vision and Pattern Recognitio

Memory architecture for efficient utilization of SDRAM: a case study of the computation/memory access trade-off

This paper discusses the trade-off between calculations and memory accesses in a 3D graphics tile renderer for visualization of data from medical scanners. The performance requirement of this application is a frame rate of 25 frames per second when rendering 3D models with 2 million triangles, i.e. 50 million triangles per second, sustained (not peak). At present, a software implementation is capable of 3-4 frames per second for a 1 million triangle model