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This book presents research trends on computer vision, especially on application of robotics, and on advanced approachs for computer vision (such as omnidirectional vision). Among them, research on RFID technology integrating stereo vision to localize an indoor mobile robot is included in this book. Besides, this book includes many research on omnidirectional vision, and the combination of omnidirectional vision with robotics. This book features representative work on the computer vision, and it puts more focus on robotics vision and omnidirectioal vision. The intended audience is anyone who wishes to become familiar with the latest research work on computer vision, especially its applications on robots. The contents of this book allow the reader to know more technical aspects and applications of computer vision. Researchers and instructors will benefit from this book.
This book provides a comprehensive introduction to the computational material that forms the underpinnings of the currently evolving set of brain models. It is now clear that the brain is unlikely to be understood without recourse to computational theories. The theme of An Introduction to Natural Computation is that ideas from diverse areas such as neuroscience, information theory, and optimization theory have recently been extended in ways that make them useful for describing the brains programs. This book provides a comprehensive introduction to the computational material that forms the underpinnings of the currently evolving set of brain models. It stresses the broad spectrum of learning ...
An argument that the complexities of brain function can be understood hierarchically, in terms of different levels of abstraction, as silicon computing is. The vast differences between the brain's neural circuitry and a computer's silicon circuitry might suggest that they have nothing in common. In fact, as Dana Ballard argues in this book, computational tools are essential for understanding brain function. Ballard shows that the hierarchical organization of the brain has many parallels with the hierarchical organization of computing; as in silicon computing, the complexities of brain computation can be dramatically simplified when its computation is factored into different levels of abstrac...
This book brings together the biology and computational features of the basal ganglia and their related cortical areas along with select examples of how this knowledge can be integrated into neural network models. Recent years have seen a remarkable expansion of knowledge about the anatomical organization of the part of the brain known as the basal ganglia, the signal processing that occurs in these structures, and the many relations both to molecular mechanisms and to cognitive functions. This book brings together the biology and computational features of the basal ganglia and their related cortical areas along with select examples of how this knowledge can be integrated into neural network...
Intelligent robotics has become the focus of extensive research activity. This effort has been motivated by the wide variety of applications that can benefit from the developments. These applications often involve mobile robots, multiple robots working and interacting in the same work area, and operations in hazardous environments like nuclear power plants. Applications in the consumer and service sectors are also attracting interest. These applications have highlighted the importance of performance, safety, reliability, and fault tolerance. This volume is a selection of papers from a NATO Advanced Study Institute held in July 1989 with a focus on active perception and robot vision. The papers deal with such issues as motion understanding, 3-D data analysis, error minimization, object and environment modeling, object detection and recognition, parallel and real-time vision, and data fusion. The paradigm underlying the papers is that robotic systems require repeated and hierarchical application of the perception-planning-action cycle. The primary focus of the papers is the perception part of the cycle. Issues related to complete implementations are also discussed.
"The Computational Brain addresses a broad audience: neuroscientists, computer scientists, cognitive scientists, and philosophers. It is written for both the expert and novice. A basic overview of neuroscience and computational theory is provided, followed by a study of some of the most recent and sophisticated modeling work in the context of relevant neurobiological research. Technical terms are clearly explained in the text, and definitions are provided in an extensive glossary. The appendix contains a précis of neurobiological techniques."--Jacket.
Neural Networks for Perception, Volume 2: Computation, Learning, and Architectures explores the computational and adaptation problems related to the use of neuronal systems, and the corresponding hardware architectures capable of implementing neural networks for perception and of coping with the complexity inherent in massively distributed computation. This book addresses both theoretical and practical issues related to the feasibility of both explaining human perception and implementing machine perception in terms of neural network models. The text is organized into two sections. The first section, computation and learning, discusses topics on learning visual behaviors, some of the elementa...
NEW FOREWORD BY JANELLE MONÁE Selected by The Atlantic as one of THE GREAT AMERICAN NOVELS. From the New York Times bestselling author of Parable of the Sower and MacArthur “Genius” Grant, Nebula, and Hugo award winner The visionary time-travel classic whose Black female hero is pulled through time to face the horrors of American slavery and explores the impacts of racism, sexism, and white supremacy then and now. “I lost an arm on my last trip home. My left arm.” Dana’s torment begins when she suddenly vanishes on her 26th birthday from California, 1976, and is dragged through time to antebellum Maryland to rescue a boy named Rufus, heir to a slaveowner’s plantation. She soon r...
November 28-December 1, 1994, Denver, Colorado NIPS is the longest running annual meeting devoted to Neural Information Processing Systems. Drawing on such disparate domains as neuroscience, cognitive science, computer science, statistics, mathematics, engineering, and theoretical physics, the papers collected in the proceedings of NIPS7 reflect the enduring scientific and practical merit of a broad-based, inclusive approach to neural information processing. The primary focus remains the study of a wide variety of learning algorithms and architectures, for both supervised and unsupervised learning. The 139 contributions are divided into eight parts: Cognitive Science, Neuroscience, Learning ...