Abstract. Robust foreground object segmentation via background modelling is a difficult problem in cluttered environments, where obtaining a clear view of the background to model i...
Vikas Reddy, Conrad Sanderson, Andres Sanin, Brian...
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
Uniform random sample is often useful in analyzing data. Usually taking a uniform sample is not a problem if the entire data resides in one location. However, if the data is distr...
The notion of using context information for solving high-level vision and medical image segmentation problems has been increasingly realized in the field. However, how to learn a...
We provide a reconstruction of Blum and Furst’s Graphplan algorithm, and use the reconstruction to extend and improve the original algorithm in several ways. In our reconstructi...