Abstract. In this paper, we consider two new online optimization problems (each with several variants), present similar online algorithms for both, and show that one reduces to the...
In the paper, a new optimal learning algorithm for a neo-fuzzy neuron (NFN) is proposed. The algorithm is characteristic in that it provides online tuning of not only the synaptic...
Abstract. Active Shape Models are commonly used to recognize and locate different aspects of known rigid objects. However, they require an off-line learning stage, such that the ex...
Michael Fussenegger, Peter M. Roth, Horst Bischof,...
We introduce confidence-weighted linear classifiers, which add parameter confidence information to linear classifiers. Online learners in this setting update both classifier param...
Online adaptation is a key requirement for image processing applications when used in dynamic environments. In contrast to batch learning, where retraining is required each time a...