The research reported in the paper aims the development of some methodologies for noise removal in image restoration. In real life, there is always some kind of noise present in the observed data. Therefore, it has been proposed that the ICA model used in image restoration should include noise...

In this paper, region based stereo matching algorithms are developed for extraction depth information from two colour stereo image pair of waste bin. Depth calculation technique from a disparity map is a key part of this study. A filter eliminating unreliable disparity estimation was used for...

The detection of remote homologies is of major importance for molecular biology applications like drug discovery. The problem is still very challenging even for state-of-the-art probabilistic models of protein families, namely Profile HMMs. In order to improve remote homology detection we...

Since in the feature space the eigenvector is a linear combination of all the samples from the training sample set, the computational efficiency of KPCA-based feature extraction falls as the training sample set grows. In this paper, we propose a novel KPCA-based feature extraction method that...

An important feature of neural networks is the ability they have to learn from their environment, and, through learning to improve performance in some sense. In the following we restrict the development to the problem of feature extracting unsupervised neural networks derived on the base of the...

This paper presents a document classifier based on text content features and its application to email classification. We test the validity of a classifier which uses Principal Component Analysis Document Reconstruction (PCADR), where the idea is that principal component analysis (PCA) can...

A Hidden Markov Model (HMM) is used to classify an out of sample <p> observation vector into either of two regimes. This leads to a procedure for making probability forecasts for changes of regimes in a time series, i.e. for turning points. <p> Instead o maximizing a likelihood, the model is estimated...</p></p>

An important application of gene expression microarray data is classification of biological samples or prediction of clinical and other outcomes. One necessary part of multivariate statistical analysis in such applications is dimension reduction. This paper provides a comparison study of three...