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The papers in this volume comprise the refereed proceedings of the conference ‘ Artificial Intelligence in Theory and Practice’ (IFIP AI 2008), which formed part of the 20th World Computer Congress of IFIP, the International Federation for Information Processing (WCC-2008), in Milan, Italy in September 2008. The conference is organised by the IFIP Technical Committee on Artificial Intelligence (Technical Committee 12) and its Working Group 12.5 (Artificial Intelligence Applications). All papers were reviewed by at least two members of our Program Committee. Final decisions were made by the Executive Program Committee, which comprised John Debenham (University of Technology, Sydney, Australia), Ilias Maglogiannis (University of Aegean, Samos, Greece), Eunika Mercier-Laurent (KIM, France) and myself. The best papers were selected for the conference, either as long papers (maximum 10 pages) or as short papers (maximum 5 pages) and are included in this volume. The international nature of IFIP is amply reflected in the large number of countries represented here. The conference also featured invited talks by Prof. Nikola Kasabov (Auckland University of Technology, New Zealand) and Prof. Lorenza Saitta (University of Piemonte Orientale, Italy). I should like to thank the conference chair, John Debenham for all his efforts and the members of our program committee for reviewing papers to a very tight deadline.
This book provides a detailed understanding of the broad issues in artificial intelligence and a survey of current AI technology. The author delivers broad coverage of innovative representational techniques, including neural networks, image processing and probabilistic reasoning, alongside the traditional methods of symbolic reasoning. The work is intended for students in artificial intelligence, researchers and LISP programmers.
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This book highlights the latest advances in the field of artificial intelligence and related technologies, with a special focus on sustainable development and environmentally friendly artificial intelligence applications. Discussing theory, applications and research, it covers all aspects of artificial intelligence in the context of sustainable development.
This book combines academic research with practical guidelines in methods and techniques to supplement existing knowledge relating to organizational management in the era of digital acceleration. It offers a simple layout with concise but rich content presented in an engaging, accessible style and the authors' holistic approach is unique in the field. From a universalist perspective, the book examines and analyzes the development of, among others, Industry 4.0, artificial intelligence (AI), AI 2.0, AI systems and platforms, algorithmics, new paradigms of organization management, business ecosystems, data processing models in AI-based organizations and AI strategies in the global perspective. An additional strength of the book is its relevance and contemporary nature, featuring information, data, forecasts or scenarios reaching up to 2030. How does one build, step by step, an organization that will be based on artificial intelligence technology and gain measurable benefits from it, for instance, as a result of its involvement in the creation of the so-called mesh ecosystem? The answer to this and many other pertinent questions are provided in this book. This timely and important book will appeal to scholars and students across the fields of organizational management and innovation and technology management, as well as managers, educators, scientists, entrepreneurs, innovators and more.
"This book highlights the development of robust and effective vision-based motion understanding systems, addressing specific vision applications such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval"--Provided by publisher.
Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.
Choice Recommended Title, January 2021 This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective
This volume provides comprehensive single-volume coverage of both the theory and the applications of knowledge-based systems.
This book constitutes the thoroughly refereed proceedings of the 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, held in Graz, Austria, in July 2019. The 41 full papers and 32 short papers presented were carefully reviewed and selected from 151 submissions. The IEA/AIE 2019 conference will continue the tradition of emphasizing on applications of applied intelligent systems to solve real-life problems in all areas. These areas include engineering, science, industry, automation and robotics, business and finance, medicine and biomedicine, bioinformatics, cyberspace, and human-machine interactions. IEA/AIE 2019 will have a special focus on automated driving and autonomous systems and also contributions dealing with such systems or their verification and validation as well.