Compositional Scheduling Analysis couples local scheduling analysis via event streams. While local analysis has successfully been extended to include hierarchical scheduling strat...
We investigate the automatic labelling of “events” from an audio recording of a sports game. We describe a technique that utilises a hierarchy of language models, which are a ...
This paper extends the methodology of analytic real-time analysis of distributed embedded systems towards merging and extracting sub-streams based on event type information. For e...
Simon Perathoner, Tobias Rein, Lothar Thiele, Kai ...
Abstract— Activity recognition in video streams is increasingly important for both the computer vision and artificial intelligence communities. Activity recognition has many app...
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...