The Asynchronous Hidden Markov Model (AHMM) models the joint likelihood of two observation sequences, even if the streams are not synchronised. We explain this concept and how the...
Marc Al-Hames, Claus Lenz, Stephan Reiter, Joachim...
Abstract. Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all p...
This paper describes work-in-progress on an Interactive Sonification Toolkit which has been developed in order to aid the analysis of general data sets. The toolkit allows the des...
Image-based rendering data sets, such as light fields, require efficient compression due to their large data size, but also easy random access when rendering from the data set. Ef...
Linguists have long been producing grammatical decriptions of yet undescribed languages. This is a time-consuming process, which has already adapted to improved technology for rec...