We describe a kernel method which uses the maximization of Onicescu’s informational energy as a criteria for computing the relevances of input features. This adaptive relevance d...
Input feature ranking and selection represent a necessary preprocessing stage in classification, especially when one is required to manage large quantities of data. We introduce a ...
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...
Intensity inhomogeneities often occur in real-world images and may cause considerable difficulties in image segmentation. In order to overcome the difficulties caused by intensity ...
Chunming Li, Chiu-Yen Kao, John C. Gore, Zhaohua D...
This paper proposes a novel method for segmenting lips from face images or video sequences. A non-linear learning method in the form of an SVM classifier is trained to recognise l...