We present an approach for learning models that obtain accurate classification of large scale data objects, collected in spatiotemporal domains. The model generation is structured ...
Igor Vainer, Sarit Kraus, Gal A. Kaminka, Hamutal ...
Climate change has been a challenging and urgent research problem for many related research fields. Climate change trends and patterns are complex, which may involve many factors a...
Abstract. We propose a novel unsupervised transfer learning framework that utilises unlabelled auxiliary data to quantify and select the most relevant transferrable knowledge for r...
—This paper presents a study of gradient estimation methods for rendering unstructured-mesh volume data. Gradient estimation is necessary for rendering shaded isosurfaces and spe...
In this paper we demonstrate a fully automated approach for discovering and monitoring patterns of daily activities. Discovering patterns of daily activities and tracking them can...