We have witnessed great interest and a wealth of promise in content-based image retrieval
as an emerging technology. While the last decade laid foundation to such promise, it also …

An overview of statistical and information-theoretic aspects of hidden Markov processes
(HMPs) is presented. An HMP is a discrete-time finite-state homogeneous Markov chain …

This chapter provides the background material and literature review for supervised
sequence labelling. Section 2.1 briefly reviews supervised learning in general. Section 2.2 …

Automatic linguistic indexing of pictures is an important but highly challenging problem for
researchers in computer vision and content-based image retrieval. In this paper, we …

The aims of this paper are two-fold: to define Gaussian mixture models (GMMs) of colored
texture on several feature spaces and to compare the performance of these models in …

Recurrent neural networks (RNNs) have proved effective at one dimensional sequence
learning tasks, such as speech and online handwriting recognition. Some of the properties …

Markov models are extremely useful as a general, widely applicable tool for many areas in
statistical pattern recognition. This unique text/reference places the formalism of Markov …

A survey of the literature reveals that image processing tools aimed at supplementing the art
historian's toolbox are currently in the earliest stages of development. To jump-start the …

Transposable elements (TEs) are mobile, repetitive sequences that make up significant
fractions of metazoan genomes. Despite their near ubiquity and importance in genome and …

Abstract The Self-Organizing Map (SOM) algorithm has attracted a great deal of interest
among researches and practitioners in a wide variety of fields. The SOM has been analyzed …