In this paper, we propose a new classification method using composite features, each of which consists of a number of primitive features. The covariance of two composite features contains information on statistical dependency among multiple primitive features. A new discriminant analysis (C-LDA) using the covariance of composite features is a generalization of the linear discriminant analysis (...

In this paper neural networks for Nonlinear Discrimi nant Analysis in continuous speech recognition are pre sented Multilayer Perceptrons are used to estimate a posteriori probabilities for Hidden Markov Model states which are the optimal discriminant features for the sepa ration of the HMM states The a posteriori probabilities are transformed by a principal component analysis to calcu late the...

A self-organizing framework for object recognition is described. We describe a hierarchical database structure for image retrieval. The Self-Organizing Hierarchical Optimal Subspace Learning and Inference Framework (SHOSLIF) system uses the theories of optimal linear projection for automatic optimal feature derivation and a hierarchical structure to achieve a logarithmic retrieval complexity. A...

In this article, scale and orientation invariant object detection is performed by matching intensity level histograms. Unlike other global measurement methods, the present one uses a local feature description that allows small changes in the histogram signature, giving robustness to partial occlusions. Local features over the object histogram are extracted during a Boosting learning phase, sele...

In this paper a novel approach to performing classification is presented. Discriminant functions are constructed by combining selected features from the feature set with simple mathematical functions such as +; ; ; ; max; min. These discriminant functions are capable of forming nonlinear discontinuous hypersurfaces . For multimodal data more than one discriminant function may be combined with l...

AIMS To investigate whether counting cells containing immunoglobulin (Ig) subclass in colonic biopsy specimens of patients with chronic inflammatory bowel disease, in addition to conventional histological evaluation, can improve the differentiation of patients with Crohn's disease from those with ulcerative colitis. METHODS The colonic and rectal biopsy specimens of 40 patients with chronic i...

For emotion recognition, we selected pitch, log energy, formant, mel-band energies, and mel frequency cepstral coefficients (MFCCs) as the base features, and added velocity/acceleration of pitch and MFCCs to form feature streams. We extracted statistics used for discriminative classifiers, assuming that each stream is a one-dimensional signal. Extracted features were analyzed by using quadratic...

A self-organizing framework for object recognition is described. We describe a hierarchical database structure for image retrieval. The SHOSLIF (Self-Organizing Hierarchical Optimal Subspace Learning and Inference Framework) system uses the theories of optimal linear projection for automatic optimal feature derivation and a hierarchical structure to achieve a logarithmic retrieval complexity. A...

The WeDiBaDis package provides a user friendly environment to perform discriminant analysis (supervised classification). WeDiBaDis is an easy to use package addressed to the biological and medical communities, and in general, to researchers interested in applied studies. It can be suitable when the user is interested in the problem of constructing a discriminant rule on the basis of distances b...