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Pattern Recognition
This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated in this edition: semi-supervised learning, combining clustering algorithms, and relevance feedback. · Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques· Many more diagrams included--now in two color--to pr...
Pattern Recognition
Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to "learn" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10 years of teaching experience, the text was developed by the authors through use in their own classrooms.*Approaches pattern recognition from the designer's point of view*New edition highlights latest developments in this growing field, including independent components and support vector machines, not available elsewhere*Supplemented by computer examples selected from applications of interest
Introduction to Pattern Recognition
Introduction to Pattern Recognition: A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas' Pattern Recognition. It includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision. - Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition, Fourth Edition - Solved examples in Matlab, including real-life data sets in imaging and audio recognition - Available separately or at a special package price with the main text (ISBN for package: 978-0-12-374491-3)
Pattern Recognition
Pattern recognition is a fast growing area with applications in a widely diverse number of fields such as communications engineering, bioinformatics, data mining, content-based database retrieval, to name but a few. This new edition addresses and keeps pace with the most recent advancements in these and related areas. This new edition: a) covers Data Mining, which was not treated in the previous edition, and is integrated with existing material in the book, b) includes new results on Learning Theory and Support Vector Machines, that are at the forefront of today's research, with a lot of interest both in academia and in applications-oriented communities, c) for the first time treats audio al...
Pattern Recognition & Matlab Intro
This specially priced set includes a copy of Theodoridis/Koutroumbas, Pattern Recognition 4e and Theodoridis/Pikrakis/Koutroumbas/Cavouras, Introduction to Pattern Recognition: A Matlab Approach. The main text provides breadth and depth of coverage of pattern recognition theory and application, including modern topics like non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, and combining clustering algorithms. Together with worked examples, exercises, and Matlab applications it provides the most comprehensive coverage currently available. The accompanying manual includes MATLAB code of the most common methods and algorithms in the book, together with a descriptive summary and solved problems, and including real-life data sets in imaging and audio recognition.
Machine Learning and Its Applications
In recent years machine learning has made its way from artificial intelligence into areas of administration, commerce, and industry. Data mining is perhaps the most widely known demonstration of this migration, complemented by less publicized applications of machine learning like adaptive systems in industry, financial prediction, medical diagnosis and the construction of user profiles for Web browsers. This book presents the capabilities of machine learning methods and ideas on how these methods could be used to solve real-world problems. The first ten chapters assess the current state of the art of machine learning, from symbolic concept learning and conceptual clustering to case-based reasoning, neural networks, and genetic algorithms. The second part introduces the reader to innovative applications of ML techniques in fields such as data mining, knowledge discovery, human language technology, user modeling, data analysis, discovery science, agent technology, finance, etc.
Evolutionary Data Clustering: Algorithms and Applications
This book provides an in-depth analysis of the current evolutionary clustering techniques. It discusses the most highly regarded methods for data clustering. The book provides literature reviews about single objective and multi-objective evolutionary clustering algorithms. In addition, the book provides a comprehensive review of the fitness functions and evaluation measures that are used in most of evolutionary clustering algorithms. Furthermore, it provides a conceptual analysis including definition, validation and quality measures, applications, and implementations for data clustering using classical and modern nature-inspired techniques. It features a range of proven and recent nature-inspired algorithms used to data clustering, including particle swarm optimization, ant colony optimization, grey wolf optimizer, salp swarm algorithm, multi-verse optimizer, Harris hawks optimization, beta-hill climbing optimization. The book also covers applications of evolutionary data clustering in diverse fields such as image segmentation, medical applications, and pavement infrastructure asset management.
Pattern Recognition - Applications and Methods
This edited book includes extended and revised versions of a set of selected papers from the First International Conference on Pattern Recognition (ICPRAM 2012), held in Vilamoura, Algarve, Portugal, from 6 to 8 February, 2012, sponsored by the Institute for Systems and Technologies of Information Control and Communication (INSTICC) and held in cooperation with the Association for the Advancement of Artificial Intelligence (AAAI) and Pattern Analysis, Statistical Modelling and Computational Learning (PASCAL2). The conference brought together researchers, engineers and practitioners interested on the areas of Pattern Recognition, both from theoretical and application perspectives.
Cybernetic Revelation
Cybernetic Revelation explores the dual philosophical histories of deconstruction and artificial intelligence, tracing the development of concepts like the "logos" and the notion of modeling the mind technologically from pre-history to contemporary thinkers like Slavoj Žižek, Steven Pinker, Bernard Stiegler and Daniel C. Dennett. The writing is clear and accessible throughout, yet the text probes deeply into major philosophers seen by JD Casten as "conceptual engineers." Philosophers covered include: Anaximander, Heraclitus, Parmenides, Plato, Aristotle, Philo, Augustine, Shakespeare, Descartes, Spinoza, Leibniz, Locke, Berkeley, Hume, Kant, Hegel, Nietzsche, Freud, Jung, Joyce, Dewey, Wittgenstein, Heidegger, Adorno, Benjamin, Derrida, Chomsky, Žižek, Pinker, Dennett, Hofstadter, Stiegler + more; with special chapters on: AI's history, Complexity, Deconstructing AI, Aesthetics, Consciousness + more...
Advances in Artificial Intelligence: Theories, Models, and Applications
This volume constitutes the refereed proceedings of the 6th Hellenic Conference on Artificial Intelligence, SETN 2010, held in Athens, Greece, in May 2010. The 28 revised full papers and 22 revised short papers presented were carefully reviewed and selected from 83 submissions. The topics include but are not restricted to adaptive systems; AI and creativity; AI architectures; artificial life; autonomous systems; data mining and knowledge discovery; hybrid intelligent systems & methods; intelligent agents, multi-agent systems; intelligent distributed systems; intelligent information retrieval; intelligent/natural interactivity, intelligent virtual environments; knowledge representation and reasoning, logic programming; knowledge-based systems; machine learning, neural nets, genetic algorithms; natural language processing; planning and scheduling; problem solving, constraint satisfaction; robotics, machine vision, machine sensing.
