Learning visual classifiers for object recognition from weakly labeled data requires determining correspondence between image regions and semantic object classes. Most approaches u...
Multi-document summarization aims to create a compressed summary while retaining the main characteristics of the original set of documents. Many approaches use statistics and mach...
Dingding Wang, Tao Li, Shenghuo Zhu, Chris H. Q. D...
A typical way to perform video annotation requires to classify video elements (e.g. events and objects) according to some pre-defined ontology of the video content domain. Ontolo...
In this paper we present a statistical learning scheme for image classification based on a mixture of old fashioned ideas and state of the art learning tools. We represent input i...
We introduce the posterior probabilistic clustering (PPC), which provides a rigorous posterior probability interpretation for Nonnegative Matrix Factorization (NMF) and removes th...