Most of previous approaches to automatic prosodic event detection are based on supervised learning, relying on the availability of a corpus that is annotated with the prosodic lab...
We develop a mixture-based approach to robust density modeling and outlier detection for experimental multivariate data that includes measurement error information. Our model is d...
For large scale automatic semantic video characterization, it is necessary to learn and model a large number of semantic concepts. But a major obstacle to this is the insufficienc...
According to some current thinking, a very large number of semantic concepts could provide researcher a novel way to characterize video and be utilized for video retrieval and und...
Mining evolving data streams for concept drifts has gained importance in applications like customer behavior analysis, network intrusion detection, credit card fraud detection. Se...