From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

Fast Fourier Transform

Computer algebra systems are now ubiquitous in all areas of science and engineering. This highly successful textbook, widely regarded as the “bible of computer algebra”, gives a thorough introduction to the algorithmic basis of the mathematical engine in computer algebra systems. Designed to accompany oneor two-semester courses for advanced undergraduate or graduate students in computer science or mathematics, its comprehensiveness and reliability has also made it an essential reference for professionals in the area. Special features include: detailed study of algorithms including time analysis; implementation reports on several topics; complete proofs of the mathematical underpinnings; and a wide variety of applications (among others, in chemistry, coding theory, cryptography, computational logic, and the design of calendars and musical scales). A great deal of historical information and illustration enlivens the text. In this third edition, errors have been corrected and much of the Fast Euclidean Algorithm chapter has been renovated.

Modern computer algebra

The Artificial Intelligence field continues to be plagued by what can only be described as ‘bold promises for the future syndrome’, often perpetrated by researchers who should know better. While impartial assessment can point to concrete contributions over the past 50 years (such as automated theorem proving, games strategies, the LISP and Prolog high-level computer languages, Automatic Speech Recognition, Natural Language Processing, mobile robot path planning, unmanned vehicles, humanoid robots, data mining, and more), the more cynical argue that AI has witnessed more than its fair share of ‘unmitigated disasters’ during this time – see, for example [3,58,107,125,186]. The general public becomes rapidly jaded with such ‘bold predictions’ that fail to live up to their original hype, and which ultimately render the zealots’ promises as counter-productive.

Computational Intelligence: An Introduction

This paper presents some results in the implementation of a local navigation strategy for environment exploration using real robot. As an experiment platform we used mini-robot Khepera II running in the Teleworkbench. The complete environment is divided into small quadratic patches with some objects placed in it. With on-board infrared sensors and wheel encoder, the robot can successfully explore the unknown environment. Moreover, by calculating the distance of surrounding patches, the implemented algorithm will minimize the distance traveled, in turn less energy and time. This paper also shows the advantage of using the Teleworkbench for performing experiments using real robots.

Environment Exploration Using Mini-Robot Khepera

The effort spent on adapting existing networks to new applications has motivated the automated architecture search. Network structures discovered with evolutionary or other search algorithms have surpassed hand-crafted image classifiers in terms of accuracy. However, these approaches do not constrain certain characteristics like network size, which leads to unnecessary computational effort. Thus, this work shows that generational evolutionary algorithms can be used for a constrained exploration of convolutional network architectures to create a selection of networks for a specific application or target architecture.

Constraint Exploration of Convolutional Network Architectures with Neuroevolution

Hyperspectral imaging has been proven to be a viable tool for automated food inspection that is non-invasive and on-line capable. In this contribution a hardware implemented Self-Organizing Feature Map with Conscience (CSOM) is presented that is capable of on-line adaptation and recall in order to learn to classify green coffee varieties as well as coffee of different roast stages. The CSOM showed favourable results in some datasets compared to a number of classical supervised neural network classifiers. The massive parallel neural hardware architecture allows for constant processing times at different map sizes.

Hardware accelerated real time classification of hyperspectral imaging data for coffee sorting

Mit Hilfe von selbstorganisierenden Karten, die einen speziellen Typ von kunstlichen neuronalen Netzen darstellen, konnen Parameter aus einem Prozes klassifiziert und korreliert werden. Neben dem Funktionsprinzip dieser Karten werden neue, besonders effektive Algorithmen beschrieben. Am Beispiel von Parametern aus einer VLSI-Prozeslinie werden die Auswertung der Parameter, die Prozesuberwachung und die Voraussage uber die zu erwartenden Ergebnisse bei verschiedenen Prozesvarianten mit Hilfe einer 50 x 50 Karte besprochen. Es zeigt sich, das es nur aufgrund der Selbstorganisation zu einer intelligenten Datenauswertung kommt. Daher konnen solche Karten als Akzeleratoren in einem Expertensystem eingesetzt werden.

Ulrich Rückert

Papers

Environment Exploration Using Mini-Robot Khepera

Constraint Exploration of Convolutional Network Architectures with Neuroevolution

Hardware accelerated real time classification of hyperspectral imaging data for coffee sorting

Selbstorganisierende Parameterkarten zur Prozeßüberwachung und -voraussage

Detection of Body Movement and Measurement of Physiological Stress with a Mobile Chest Module in Obesity Prevention