We present similarity-based methods to cluster digital photos by time and image content. The approach is general, unsupervised, and makes minimal assumptions regarding the structu...
Matthew L. Cooper, Jonathan Foote, Andreas Girgens...
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Subspace learning techniques are widespread in pattern recognition research. They include PCA, ICA, LPP, etc. These techniques are generally linear and unsupervised. The problem o...
Recent interest in the use of software character agents raises the issue of how many agents should be used in online learning. In this paper we review evidence concerning the rela...
The issue of initializing the model of a new student is of great importance for educational applications that aim at offering individualized support to students. In this paper we ...