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Perceptual processes in humans and machines, investigated and simulated by means of the computational approach, are the subject matter of this volume. Researchers in artificial intelligence, pattern recognition, and psychology discuss aspects of vision, speech understanding, sensory-motor coordination, and their interplay with cognitive and behavioral functionalities. The papers adopt the computational approach as the basic research paradigm. Connectionist models, numerical and statistical techniques, symbolic (logic-based) formalisms, and hybrid representations provide the formal background to the research. Some of the papers were prepared for a workshop held in Trieste, Italy, in October 1992.
The Secret Behind Our Perceptions Finally Revealed! Why do we gravitate to products endorsed by celebrities? Why does time seem to go by faster as we get older? Why are some athletes perpetual winners and others losers? Exploring the brain’s ability to interpret and make sense of the world, Dr. Brian Boxer Wachler describes how your perception can be reality or fantasy and how to separate the two, which is the basis of improving your Perceptual Intelligence (PI). With concrete examples and case studies, Dr. Brian (as he’s known to his patients) explains why our senses do not always match reality and how we can influence the world around us through perceptions, inward and outward. By fine-tuning your PI, you can better understand what’s really going on and make more insightful decisions in your life.
The rise of technology has led to rapid developments in robotic intelligence and its various applications. The success or failure of these systems is linked closely with effective perception and cognition models. Aligning Perceptual and Conceptual Information for Cognitive Contextual System Development: Emerging Research and Opportunities is an innovative source of academic content on approaches to cognitive and perceptual systems development in artificial intelligence. Including a range of relevant topics such as object processing, implicit symbols, and knowledge representation, this book is ideally designed for engineers, academics, practitioners, and students interested in perceptual and conceptual interpretation in artificial intelligence.
Design of cognitive systems for assistance to people poses a major challenge to the fields of robotics and artificial intelligence. The Cognitive Systems for Cognitive Assistance (CoSy) project was organized to address the issues of i) theoretical progress on design of cognitive systems ii) methods for implementation of systems and iii) empirical studies to further understand the use and interaction with such systems. To study, design and deploy cognitive systems there is a need to considers aspects of systems design, embodiment, perception, planning and error recovery, spatial insertion, knowledge acquisition and machine learning, dialog design and human robot interaction and systems integration. The CoSy project addressed all of these aspects over a period of four years and across two different domains of application – exploration of space and task / knowledge acquisition for manipulation. The present volume documents the results of the CoSy project. The CoSy project was funded by the European Commission as part of the Cognitive Systems Program within the 6th Framework Program.
Explore the cutting-edge of neuromorphic technologies with applications in Artificial Intelligence In Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics, a team of expert engineers delivers a comprehensive discussion of all aspects of neuromorphic electronics designed to assist researchers and professionals to understand and apply all manner of brain-inspired computing and perception technologies. The book covers both memristic and neuromorphic devices, including spintronic, multi-terminal, and neuromorphic perceptual applications. Summarizing recent progress made in five distinct configurations of brain-inspired computing, the authors explore this promising technology’s potential applications in two specific areas: neuromorphic computing systems and neuromorphic perceptual systems. The book also includes: A thorough introduction to two-terminal neuromorphic memristors, including memristive devices and resistive switching mechanisms Comprehensive explorations of spintronic neuromorphic devices and multi-terminal neuromorphic devices with cognitive behaviors Practical discussions of neuromorphic devices based on chalcogenide and organic materials In-depth examinations of neuromorphic computing and perceptual systems with emerging devices Perfect for materials scientists, biochemists, and electronics engineers, Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics will also earn a place in the libraries of neurochemists, neurobiologists, and neurophysiologists.
This book constitutes the refereed proceedings of the First International Symposium on Handheld and Ubiquitous Computing, HUC'99, held in Karlsruhe, Germany in September 1999. The 23 revised full papers presented together with four invited keynote contributions, 26 reviewed posters, and two panel statements were carefully reviewed and selected from a large number of paper submissions. The papers are organized in topical sections on handheld and wearable appliances, location-based services, smart devices and smart environments, handhelds in distributed systems, handheld and wearable CSCW, context-aware mobile applications, interacting with environment, and interacting with handhelds.
Robotic perception is related to many applications in robotics where sensory data and artificial intelligence/machine learning (AI/ML) techniques are involved. Examples of such applications are object detection, environment representation, scene understanding, human/pedestrian detection, activity recognition, semantic place classification, object modeling, among others. Robotic perception, in the scope of this chapter, encompasses the ML algorithms and techniques that empower robots to learn from sensory data and, based on learned models, to react and take decisions accordingly. The recent developments in machine learning, namely deep-learning approaches, are evident and, consequently, robotic perception systems are evolving in a way that new applications and tasks are becoming a reality. Recent advances in human-robot interaction, complex robotic tasks, intelligent reasoning, and decision-making are, at some extent, the results of the notorious evolution and success of ML algorithms. This chapter will cover recent and emerging topics and use-cases related to intelligent perception systems in robotics.
Published in honour of the 70th birthday of Yoh-Han Pao, George S. Dively Dis tinguished Professor of Engineering at Case Western Reserve University, Cleveland, Ohio, this festschrift embraces a remarkably diverse set of topics. Drawing from the fields of pattern recognition, engineering, artificial intelligence and artificial neural systems, it is a fitting testament to the extraordinary breadth of his professional in terests both in foundational research into the new technology of Intelligent Systems and ill the application of that evolving technology to the solution of hard engineering problems. In common with many scientists who build their reputations in one field before devoting their considerable energies and talents to another one, by 1972, the year in which I met him for the first time, Yoh-Han had made significant contributions to laser technology, in particular to the development of the highly accurate and stable lasers required for holographic recording purposes. In conventional holography, the information stored in a hologram produces a virtual image of the object charac terised by it. However, Yoh-Han became fascinated by the possiblity of driving the process hackwards, of using the hologram as an associative memory device enabling previously stored information to be retrieved on the basis of partial cues. It was this burgeoning interest which shaped his career for more than twenty years. Just prior to 1972, my colleagues Professor Christopher Longuet-Higgins and Dr.