The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
We propose a new unsupervised learning technique for extracting information about authors and topics from large text collections. We model documents as if they were generated by a...
Michal Rosen-Zvi, Chaitanya Chemudugunta, Thomas L...
Any automated decision support software must tailor its actions or recommendations to the preferences of different users. Thus it requires some representation of user preferences ...
Online communities have become popular for publishing and searching content, as well as for finding and connecting to other users. User-generated content includes, for example, pe...
Ralf Schenkel, Tom Crecelius, Mouna Kacimi, Sebast...
Abstract. This paper proposes a novel method to deal with the representation issue in texture classification. A learning framework of image descriptor is designed based on the Fish...