Conferences related to Artificial Intelligence

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2014 IEEE International Conference on Systems, Man and Cybernetics - SMC

SMC2014 targets advances in Systems Science and Engineering, Human-Machine Systems, and Cybernetics involving state-of-art technologies interacting with humans to provide an enriching experience and thereby improving the quality of lives including theories, methodologies, and emerging applications.

  • 2013 IEEE International Conference on Systems, Man and Cybernetics - SMC

    SMC 2013 targets advances in Systems Science and Engineering Human-machine Systems and Cybernetics involving state-of-the-art technologies interacting with humans to provide an enriching experience and thereby improving the quality of lives including theories, methodologies and emerging applications.

  • 2012 IEEE International Conference on Systems, Man and Cybernetics - SMC

    Theory, research and technology advances including applications in all aspects of systems science and engineering, human machine systems, and emerging cybernetics.

  • 2011 IEEE International Conference on Systems, Man and Cybernetics - SMC

    Theory, research, and technology advances including applications in all aspects of systems science and engineering, human machine systems, and emerging cybernetics.

  • 2010 IEEE International Conference on Systems, Man and Cybernetics - SMC

    The 2010 IEEE International Conference on Systems, Man, and Cybernetics (SMC2010) provides an international forum that brings together those actively involved in areas of interest to the IEEE Systems, Man, and Cybernetics Society, to report on up-to-the-minute innovations and developments, to summarize the state-of-the-art, and to exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics.

  • 2009 IEEE International Conference on Systems, Man and Cybernetics - SMC

    The 2009 IEEE International Conference on Systems, Man, and Cybernetics (SMC2009) provides an international forum that brings together those actively involved in areas of interest to the IEEE Systems, Man, and Cybernetics Society, to report on up-to-the-minute innovations and developments, to summarize the state-of-the-art, and to exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics.


2013 12th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

Cognitive Informatics (CI) is a cutting-edge and multidisciplinary research field that tackles the fundamental problems shared by modern informatics, computing, AI, cybernetics, computational intelligence, cognitive science, intelligence science, neuropsychology, brain science, systems science, software engineering, knowledge engineering, cognitive robots, scientific philosophy, cognitive linguistics, life sciences, and cognitive computing.

  • 2012 11th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive informatics and Cognitive Computing are a transdisciplinary enquiry on the internal information processing mechanisms and processes of the brain and their engineering applications in cognitive computers, computational intelligence, cognitive robots, cognitive systems, and in the AI, IT, and software industries. The 11th IEEE Int l Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 12) focuses on the theme of e-Brain and Cognitive Computers.

  • 2011 10th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive Informatics and Cognitive Computing are a transdisciplinary enquiry on the internal information processing mechanisms and processes of the brain and their engineering applications in cognitive computers, computational intelligence, cognitive robots, cognitive systems, and in the AI, IT, and software industries. The 10th IEEE Int l Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 11) focuses on the theme of Cognitive Computers and the e-Brain.

  • 2010 9th IEEE International Conference on Cognitive Informatics (ICCI)

    Cognitive Informatics (CI) is a cutting-edge and transdisciplinary research area that tackles the fundamental problems shared by modern informatics, computing, AI, cybernetics, computational intelligence, cognitive science, neuropsychology, medical science, systems science, software engineering, telecommunications, knowledge engineering, philosophy, linguistics, economics, management science, and life sciences.

  • 2009 8th IEEE International Conference on Cognitive Informatics (ICCI)

    The 8th IEEE International Conference on Cognitive Informatics (ICCI 09) focuses on the theme of Cognitive Computing and Semantic Mining. The objectives of ICCI'09 are to draw attention of researchers, practitioners, and graduate students to the investigation of cognitive mechanisms and processes of human information processing, and to stimulate the international effort on cognitive informatics research and engineering applications.

  • 2008 7th IEEE International Conference on Cognitive Informatics (ICCI)

    The 7th IEEE International Conference on Cognitive Informatics (ICCI 08) focuses on the theme of Cognitive Computers and Computational Intelligence. The objectives of ICCI 08 are to draw attention of researchers, practitioners and graduate students to the investigation of cognitive mechanisms and processes of human information processing, and to stimulate the international effort on cognitive informatics research and engineering applications.

  • 2007 6th IEEE International Conference on Cognitive Informatics (ICCI)

  • 2006 5th IEEE International Conference on Cognitive Informatics (ICCI)


2013 ACS International Conference on Computer Systems and Applications (AICCSA)

This International Conference on Computer Systems and Applications (AICCSA) is the premier Computer Science and Engineering Conference in the Middle East and North Africa. It is held every other year in an Arab country and intends to enhance the participation and the contribution of the Arab world in Information Technologies and to maximize its benefits. In general, the scope of AICCSA includes all aspects of the theory and practice of computer science and information technology, but, depending on the needs, specific topics and/or issues might be prioritized.

  • 2011 9th IEEE/ACS International Conference on Computer Systems and Applications (AICCSA)

    An international conference that covers a broad range of information technology areas including Bioinformatics and Biomedical Engineering, Cloud and Grid Computing, Architecture and Systems, Databases, High Performance Computing, Reconfigurable and GPU Computing,Computer Networks and Security, Energy Efficient Computing, Wireless Systems and Sensor Networks.

  • 2010 IEEE/ACS International Conference on Computer Systems and Applications (AICCSA)

    AICCSA is the premier Computer Science and Engineering Conference in the Middle East and North Africa covering new advances in computer systems and their applications. Papers will cover the theoretical, conceptual, descriptive in nature, or a survey of the state of the art.

  • 2009 IEEE/ACS International Conference on Computer Systems and Applications (AICCSA)

    ICCSA is the premier Computer Science and Engineering Conference in the Middle East and North Africa


2013 IEEE 17th International Conference on Intelligent Engineering Systems (INES)

The aim of INES conference series is to provide researchers andpractitioners from industry and academia with a platform to report on recent developments inthe area of computational intelligence.


2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA)

The ETFA conference series is the prime, and largest, IEEE-sponsored event dedicated to factory automation and emerging technologies in industrial automation.The aim of the ETFA conference series is to provide researchers and practitioners from industry and academia with a platform to report on recent developments in the newly emerging areas of technology and their potential applications to factory automation.The technical success of the ETFA conference series also testifies to the rapid evolution of the area of industrial automation in the recent decades. The proceedings of the conference give a fairly accurate picture of the state of the art of the area. ETFA conferences were fortunate to attract high quality papers, many of which were later published in the IEEE Transactions on Industrial Electronics.

  • 2012 IEEE 17th Conference on Emerging Technologies & Factory Automation (ETFA 2012)

    The ETFA conference series is the prime, and largest, IEEE-sponsored event dedicated to factory automation and emerging technologies in industrial automation. The aim of the ETFA conference series is to provide researchers and practitioners with a platform to report on recent developments and their potential applications to factory automation.

  • 2011 IEEE 16th Conference on Emerging Technologies & Factory Automation (ETFA 2011)

    The aim of ETFA conference is to bring together researchers and practitioners from the industry and academia and provide them with a platform to report on recent advances and developments in the newly emerging areas of technology, as well as actual and potential applications to industrial and factory automation

  • 2010 IEEE 15th Conference on Emerging Technologies & Factory Automation (ETFA 2010)

    The aim of the conference is to bring together researchers and practitioners from the industry and academia and provide them with a platform to report on recent advances and developments in the newly emerging areas of technology, as well as actual and potential applications to industrial and factory automation.

  • 2009 IEEE Conference on Emerging Technologies & Factory Automation (ETFA 2009)

    The aim of the conference is to bring together researchers and practitioners from the industry and academia and provide them with a platform to report on recent advances and developments in the newly emerging areas of technology, as well as actual and potential applications to industrial and factory automation.


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Periodicals related to Artificial Intelligence

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Computational Intelligence Magazine, IEEE

The IEEE Computational Intelligence Magazine (CIM) publishes peer-reviewed articles that present emerging novel discoveries, important insights, or tutorial surveys in all areas of computational intelligence design and applications.


Computer

Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.


Consumer Electronics, IEEE Transactions on

The design and manufacture of consumer electronics products, components, and related activities, particularly those used for entertainment, leisure, and educational purposes


Intelligent Systems, IEEE

IEEE Intelligent Systems, a bimonthly publication of the IEEE Computer Society, provides peer-reviewed, cutting-edge articles on the theory and applications of systems that perceive, reason, learn, and act intelligently. The editorial staff collaborates with authors to produce technically accurate, timely, useful, and readable articles as part of a consistent and consistently valuable editorial product. The magazine serves software engineers, systems ...


Intelligent Transportation Systems, IEEE Transactions on

The theoretical, experimental and operational aspects of electrical and electronics engineering and information technologies as applied to Intelligent Transportation Systems (ITS). Intelligent Transportation Systems are defined as those systems utilizing synergistic technologies and systems engineering concepts to develop and improve transportation systems of all kinds. The scope of this interdisciplinary activity includes the promotion, consolidation and coordination of ITS technical ...


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Most published Xplore authors for Artificial Intelligence

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Xplore Articles related to Artificial Intelligence

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Ontologies for Describing the Context of Scientific Experiment Processes

Rudolf Mayer; Tomasz Miksa; Andreas Rauber 2014 IEEE 10th International Conference on e-Science, 2014

The re-usability and repeatability of e-Science experiments is widely understood as a requirement of validating and reusing previous work in data- intensive domains. Experiments are, however, often complex chains of processing, involving a number of data sources, computing infrastructure, software tools, or external and third-party services, rendering repeatability a challenging task. Another important aspect of many experiments is in the ...


Face image assessment learned with objective and relative face image qualities for improved face recognition

Hyung-Il Kim; Seung Ho Lee; Yong Man Ro 2015 IEEE International Conference on Image Processing (ICIP), 2015

Considerable research efforts have been made for face recognition in various real-world applications. However, degraded face images, acquired in the real- world, make face recognition difficult. In this paper, we propose a new face image quality assessment that aims to realize a robust and reliable face recognition system. The proposed method considers two factors for face image quality, i.e., visual ...


Labelfaces: Parsing facial features by multiclass labeling with an epitome prior

Jonathan Warrell; Simon J. D. Prince 2009 16th IEEE International Conference on Image Processing (ICIP), 2009

We consider the problem of parsing facial features from an image labeling perspective. We learn a per-pixel unary classifier, and a prior over expected label configurations, allowing us to estimate a dense labeling of facial images by part (e.g. hair, mouth, moustache, hat). This approach deals naturally with large variations in shape and appearance characteristic of unconstrained facial images, and ...


The fairness of ranking procedure in pair-wise preference learning

Zhizheng Zhang; Hancheng Xing; Zhenzhen Wang; Qingjian Ni 2005 International Conference on Natural Language Processing and Knowledge Engineering, 2005

In pair-wise preference learning, a crucial point is how to decode the predictions of the pair-wise preference to a final preference order - a ranking procedure. Simple voting, iterated choice, and Slater-optimal ranking are usual techniques, but their ranking results are usually very different from each other. Hitherto, experimentation is the main method of estimating the ranking approaches, and the ...


Parts-based multi-task sparse learning for visual tracking

Zhengjian Kang; Edward K. Wong 2015 IEEE International Conference on Image Processing (ICIP), 2015

We present a novel parts-based multi-task sparse learning method for particle- filter-based tracking. In our method, candidate regions are divided into structured local parts which are then sparsely represented by a linear combination of atoms from dictionary templates. We consider parts in each particle as individual tasks and jointly incorporate intrinsic relationship between tasks across different parts and across different ...


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Educational Resources on Artificial Intelligence

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eLearning

Ontologies for Describing the Context of Scientific Experiment Processes

Rudolf Mayer; Tomasz Miksa; Andreas Rauber 2014 IEEE 10th International Conference on e-Science, 2014

The re-usability and repeatability of e-Science experiments is widely understood as a requirement of validating and reusing previous work in data- intensive domains. Experiments are, however, often complex chains of processing, involving a number of data sources, computing infrastructure, software tools, or external and third-party services, rendering repeatability a challenging task. Another important aspect of many experiments is in the ...


Face image assessment learned with objective and relative face image qualities for improved face recognition

Hyung-Il Kim; Seung Ho Lee; Yong Man Ro 2015 IEEE International Conference on Image Processing (ICIP), 2015

Considerable research efforts have been made for face recognition in various real-world applications. However, degraded face images, acquired in the real- world, make face recognition difficult. In this paper, we propose a new face image quality assessment that aims to realize a robust and reliable face recognition system. The proposed method considers two factors for face image quality, i.e., visual ...


Labelfaces: Parsing facial features by multiclass labeling with an epitome prior

Jonathan Warrell; Simon J. D. Prince 2009 16th IEEE International Conference on Image Processing (ICIP), 2009

We consider the problem of parsing facial features from an image labeling perspective. We learn a per-pixel unary classifier, and a prior over expected label configurations, allowing us to estimate a dense labeling of facial images by part (e.g. hair, mouth, moustache, hat). This approach deals naturally with large variations in shape and appearance characteristic of unconstrained facial images, and ...


The fairness of ranking procedure in pair-wise preference learning

Zhizheng Zhang; Hancheng Xing; Zhenzhen Wang; Qingjian Ni 2005 International Conference on Natural Language Processing and Knowledge Engineering, 2005

In pair-wise preference learning, a crucial point is how to decode the predictions of the pair-wise preference to a final preference order - a ranking procedure. Simple voting, iterated choice, and Slater-optimal ranking are usual techniques, but their ranking results are usually very different from each other. Hitherto, experimentation is the main method of estimating the ranking approaches, and the ...


Parts-based multi-task sparse learning for visual tracking

Zhengjian Kang; Edward K. Wong 2015 IEEE International Conference on Image Processing (ICIP), 2015

We present a novel parts-based multi-task sparse learning method for particle- filter-based tracking. In our method, candidate regions are divided into structured local parts which are then sparsely represented by a linear combination of atoms from dictionary templates. We consider parts in each particle as individual tasks and jointly incorporate intrinsic relationship between tasks across different parts and across different ...


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IEEE-USA E-Books

  • AI and Music: New Directions

    Machine Models of Music brings together representative models ranging from Mozart's "Musical Dice Game" to a classic article by Marvin Minsky and current research to illustrate the rich impact that artificial intelligence has had on the understanding and composition of traditional music and to demonstrate the ways in which music can push the boundaries of traditional Al research.Major sections of the book take up pioneering research in generate-and-test composition (Lejaren Hiller, Barry Brooks, Jr., Stanley Gill); composition parsing (Allen Forte, Herbert Simon, Terry Winograd); heuristic composition (John Rothgeb, James Moorer, Steven Smoliar); generative grammars (Otto Laske, Gary Rader, Johan Sundberg, Fred Lerdahl); alternative theories (Marvin Minsky, James Meehan); composition tools (Charles Ames, Kemal Ebcioglu, David Cope, C. Fry); and new directions (David Levitt, Christopher Longuet-Higgins, Jamshed Bharucha, Stephan Schwanauer).Stephan Schwanauer is President of Mediasoft Corporation. David Levitt is the founder of HIP Software and head of audio products at VPL Research.

  • Front Matter

    This chapter contains sections titled: Half Title, Title, Copyright, Dedication, Contents, Foreword, Preface

  • The Human Brain: Metaphor Maker

    This chapter contains sections titled: General Introduction to Brain Structure and function, Form and Function: Brain and Mind, Some Structural Elements: Brain Cells, Butterfl ies of the Soul, Some Functional Elements: Electrochemical Current and Communication among Neurons, Cellular Mechanisms for Memory Storage, Basic Organization of the Brain's Functional Regions, Techniques for Analyzing Brain Activity, Acquisition of Functional Capacities in the Brain, Some Notes on the Evolution of the Brain, Summary

  • The Human Mind: Metaphor of the World

    This chapter contains sections titled: Mind-Brain Duality, Emergent Complexity, Three Levels of Abstraction and Two Operational Spaces, Proprioception, Perception and Knowledge, Memory and Learning, The Magical Number Seven (Plus or Minus Two), Attention, Thought, Decision Making and Problem Solving, Language, Emotions, Consciousness and Qualia, Intelligence, Born or Made? Genetics or Learning, Summary

  • Artificial Intelligence: Silicon Metaphors

    This chapter contains sections titled: The Silicon Metaphor: Computer Information Processing, A Protohistory of Artificial Intelligence: A Web of Desires and Ideas, A Protohistory of Artificial Intelligence: Scientific Elements, The Modern Development of Artificial Intelligence, A Protohistory of Automatic Chess, Some Relevant Concepts: Recursiveness, Algorithms, and Heuristics, Expert Systems and Knowledge Engineering, Artificial Neural Networks, Elephants Don't Play Chess, Agents, Embodiment, and the New AI, Summary

  • Architectures, Organizational Principles, and Functional Approaches

    These sixty contributions from researchers in ethology, ecology, cybernetics, artificial intelligence, robotics, and related fields delve into the behaviors and underlying mechanisms that allow animals and, potentially, robots to adapt and survive in uncertain environments. They focus in particular on simulation models in order to help characterize and compare various organizational principles or architectures capable of inducing adaptive behavior in real or artificial animals.Jean-Arcady Meyer is Director of Research at CNRS, Paris. Stewart W. Wilson is a Scientist at The Rowland Institute for Science, Cambridge, Massachusetts.

  • Elementary Solution Methods

    Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

  • Expert Systems

    In terms of functionality, an 'expert system' can be defined as a program that relays on a bank of knowledge to perform certain specific tasks, which can be sometimes difficult, and are usually solved by the human expert in the field. The performances of an intelligent program depend primarily on the 'quality' of the knowledge base (KB) and the organization of the knowledge, which should allow the problem to be solved within an acceptable period. The part of the expert system, which performs the reasoning function, is called the 'inference engine (IE)'. This chapter considers the main characteristics that qualify a program as an expert system. Expert systems offer many advantages over a human expert. They contain these modules: the knowledge base, database, the IE, knowledge acquisition, and the software interfaces with the expert or application engineer, knowledge engineer, and user.

  • The Complete Metaphor: Chess and Problem Solving

    This chapter contains sections titled: Why Chess?, A Brief History of Chess, Who Plays Chess?, Chess: A Game? A Human Problem, Chess: An Art? An Aesthetic Problem, Chess: A Science? A Heuristic Problem, Move Choice, Chess and Cognitive Processes: First Contributions, Chess and Cognitive Processes: The Contributions of Adriaan de Groot, De Groot's Conclusions, Modern Proposals: Perception and Search, Chess and Personality: Psychological and Psychoanalytical Images of the Player, Summary

  • Index

    Machine Models of Music brings together representative models ranging from Mozart's "Musical Dice Game" to a classic article by Marvin Minsky and current research to illustrate the rich impact that artificial intelligence has had on the understanding and composition of traditional music and to demonstrate the ways in which music can push the boundaries of traditional Al research.Major sections of the book take up pioneering research in generate-and-test composition (Lejaren Hiller, Barry Brooks, Jr., Stanley Gill); composition parsing (Allen Forte, Herbert Simon, Terry Winograd); heuristic composition (John Rothgeb, James Moorer, Steven Smoliar); generative grammars (Otto Laske, Gary Rader, Johan Sundberg, Fred Lerdahl); alternative theories (Marvin Minsky, James Meehan); composition tools (Charles Ames, Kemal Ebcioglu, David Cope, C. Fry); and new directions (David Levitt, Christopher Longuet-Higgins, Jamshed Bharucha, Stephan Schwanauer).Stephan Schwanauer is President of Mediasoft Corporation. David Levitt is the founder of HIP Software and head of audio products at VPL Research.



Standards related to Artificial Intelligence

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