Matthias Nagel

Jürgen Beyerer

Matthias Richter

The book offers a thorough introduction to Pattern Recognition aimed at master and advanced bachelor students of engineering and the natural sciences. Besides classification - the heart of Pattern Recognition - special emphasis is put on features, their typology, their properties and their systematic construction. Additionally, general principles that govern Pattern Recognition are illustrated and explained in a comprehensible way. Rather than presenting a complete overview over the rapidly evolving field, the book is to clarifies the concepts so that the reader can easily understand the underlying ideas and the rationale behind the methods. For this purpose, the mathematical treatment of Pattern Recognition is pushed so far that the mechanisms of action become clear and visible, but not farther. Therefore, not all derivations are driven into the last mathematical detail, as a mathematician would expect it. Ideas of proofs are presented instead of complete proofs. From the authors’ point of view, this concept allows to teach the essential ideas of Pattern Recognition with sufficient depth within a relatively lean book. Mathematical methods explained thoroughly Extremely practical approach with many examples Based on over ten years lecture at Karlsruhe Institute of Technology For students but also for practitioners

Introduction, Features, Classifiers and Principles

Pattern Recognition

Fernando Puente León

Christian Frese

The book offers a thorough introduction to machine vision. It is organized in two parts. The first part covers the image acquisition, which is the crucial component of most automated visual inspection systems. All important methods are described in great detail and are presented with a reasoned structure. The second part deals with the modeling and processing of image signals and pays particular regard to methods, which are relevant for automated visual inspection.

Automated Visual Inspection: Theory, Practice and Applications

Machine Vision

Rüdiger Dillmann

Uwe D. Hanebeck

Tanja Schultz

The 33rd Annual German Conference on Arti?cial Intelligence (KI 2010) took place at the Karlsruhe Institute of Technology KIT, September 21–24, 2010, under the motto “Anthropomatic Systems.” In this volume you will ?nd the keynote paper and 49 papers of oral and poster presentations. The papers were selected from 73 submissions, resulting in an acceptance rate of 67%. As usual at the KI conferences, two entire days were allocated for targeted workshops—seventhis year—andone tutorial. The workshopand tutorialma- rials are not contained in this volume, but the conference website, www.ki2010.kit.edu,will provide information and references to their contents. Recent trends in AI research have been focusing on anthropomatic systems, which address synergies between humans and intelligent machines. This trend is emphasized through the topics of the overall conference program. They include learning systems, cognition, robotics, perception and action, knowledge rep- sentation and reasoning, and planning and decision making. Many topics deal with uncertainty in various scenarios and incompleteness of knowledge. Summarizing, KI 2010 provides a cross section of recent research in modern AI methods and anthropomatic system applications. We are very grateful that Jos ́ edel Mill ́ an, Hans-Hellmut Nagel, Carl Edward Rasmussen, and David Vernon accepted our invitation to give a talk.

33rd Annual German Conference on AI, Karlsruhe, Germany, September 21-24, 2010, Proceedings

KI 2010: Advances in Artificial Intelligence

Christoph Stiller

Marius Zöllner

Tobias Gindele

Der Band dokumentiert das 21. Fachgespräch Autonome Mobile Systeme (AMS 2009). Die Veranstaltung bietet Wissenschaftlern aus Forschung und Industrie ein Forum für den Gedankenaustausch und eine Basis, um Kooperationen auf diesem Forschungsgebiet zu initiieren. Die Beiträge befassen sich mit Themen wie humanoide Roboter und Flugmaschinen, Perzeption und Sensorik, Kartierung und Lokalisation, Regelung, Navigation, Lernverfahren, Systemarchitekturen sowie mit der Anwendung von autonomen mobilen Systemen.

21. Fachgespräch Karlsruhe, 3./4. Dezember 2009

Autonome Mobile Systeme 2009

Christian Kühnert

Oliver Niggemann

This Open Access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, October 23-24, 2018. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.

Selected papers from the International Conference ML4CPS 2018

Machine Learning for Cyber Physical Systems

Jürgen Beyerer

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