In the focus of this paper is a comparison of the most relevant prosodic features/feature classes for the classification of boundaries and accents in German and in English. Principal components were computed based on a large prosodic feature vector; these principal components were used as predictor variables in a Linear Discriminant analysis as well as in a Classification and Regression Tree. T...

This paper proposes a new method to compare similarities of candidate models that are fitted to different areas of a query image. This method extracts the discriminant features that are changed due to the varying pose/lighting condition of given query image, and the confidence of each model-fitting is evaluated based on how much of the discriminant features is captured in each foreground. The c...

Predicting protein-folding patterns is a challenge due to the complex structure of proteins. Many sequence encoding schemes have been proposed to extract the features of pro-tein sequences, and these features are often fused to form a new combined feature set so that it can contain various useful information. However, there usually has redundant information in the combined features. In this pap...

Local discriminant bases method is a powerful algorithmic framework for feature extraction and classification applications that is based on supervised training. It is considerably faster compared to more theoretically ideal feature extraction methods such as principal component analysis or projection pursuit. In this paper an optimization block is added to original local discriminant bases algo...

This paper introduces a novel nonlinear extension of Fisher’s classical linear discriminant analysis (FDA) known as high-order Fisher’s discriminant analysis (HOFDA). The ability of the new method to capture nonlinear relationships stems from its use of an extended polynomial space constructed out of the original features. Furthermore, a genetic algorithm (GA) is used in order to incrementally ...

-In this paper, the authors combine two algorithms for application to the recognition of unconstrained isolated handwritten numerals. The first algorithm employs a modified quadratic discriminant function utilizing direction sensitive spatial features of the numeral image. The second algorithm utilizes features derived from the profile of the character in a structural configuration to recognize...

Peinado AB, Benito PJ, Díaz V, González C, Zapico AG, Álvarez M, Maffulli N, Calderón FJ. Discriminant analysis of the speciality of elite cyclists. J. Hum. Sport Exerc. Vol. 6, No. 3, pp. 480-489, 2011. The different demands of competition coupled with the morphological and physiological characteristics of cyclists have led to the appearance of cycling specialities. The aims of this study were...

Multi-resolution images of histological sections of breast cancer tissue were analyzed using texture features of Haar- and Daubechies transform wavelets. Tissue samples analyzed were from ductal regions of the breast and included benign ductal hyperplasia, ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (CA). To assess the correlation between computerized image analysis and visua...

In this work we propose a new statistic deformable model that we call discriminant snake for 3D reconstruction in volumetric images. Our discriminant snake generalises the classical snake attracted by edge points, it deforms due to a generalised contour representation. The snake selects and classifies image features by a parametric classifier and each snaxel deforms to minimise the dissimilarit...

A method of localising objects in images is proposed. Possible conngurations are evaluated using the contour discriminant, a likelihood ratio which is derived from a probabilistic model of the feature detection process. We treat each step in this process probabilistically, including the occurrence of clutter features, and derive the observation densities for both correct \target" con-gurations ...