We devise a statistical framework for edge detection by performing a statistical analysis of zero crossings of the second derivative of an image. This analysis enables us to estim...
In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
Uncertain data are inherent in some important applications, such as environmental surveillance, market analysis, and quantitative economics research. Due to the importance of thos...
We consider the problem of PAC-learning distributions over strings, represented by probabilistic deterministic finite automata (PDFAs). PDFAs are a probabilistic model for the gen...
Large amount of uncertain data is inherent in many novel and important applications such as sensor data analysis and mobile data management. A probabilistic threshold range aggrega...