Research Notes in Neural Computing - Böcker
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The study of neural networks is enjoying a great renaissance, both in computational neuroscience, the development of information processing models of living brains, and in neural computing, the use of neurally inspired concepts in the construction of "intelligent" machines. Thus the title of this volume has two interpretations: It presents models and data on the dynamic interactions occurring in the brain, and it exhibits the dynamic interactions between research in computational neuroscience and in neural computing, as scientists seek to find common principles to guide the understanding of the living brain and the design of artificial neural networks. This collection of contributions presents the current state of research, future trends and open problems in an exciting field of today's science.
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In this book a global shape model is developed and applied to the analysis of real pictures acquired with a visible light camera under varying conditions of optical degradation. Computational feasibility of the algorithms derived from this model is achieved by analytical means. The aim is to develop methods for image understanding based on structured restoration, for example automatic detection of abnormalities. We also want to find the limits of applicability of the algorithms. This is done by making the optical degradations more and more severe until the algorithms no longer succeed in their task. This computer experiment in pattern theory is one of several. The others, LEAVES, X-RAYS, and RANGE are described elsewhere. This book is suitable for an advanced undergraduate or graduate seminar in pattern theory, or as an accompanying book for applied probability, computer vision, or pattern recognition.
Del 5 - Research Notes in Neural Computing
Artificial Neural Networks for Computer Vision
Häftad, Engelska, 1991
552 kr
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This monograph is an outgrowth of the authors' recent research on the de velopment of algorithms for several low-level vision problems using artificial neural networks. Specific problems considered are static and motion stereo, computation of optical flow, and deblurring an image. From a mathematical point of view, these inverse problems are ill-posed according to Hadamard. Researchers in computer vision have taken the "regularization" approach to these problems, where one comes up with an appropriate energy or cost function and finds a minimum. Additional constraints such as smoothness, integrability of surfaces, and preservation of discontinuities are added to the cost function explicitly or implicitly. Depending on the nature of the inver sion to be performed and the constraints, the cost function could exhibit several minima. Optimization of such nonconvex functions can be quite involved. Although progress has been made in making techniques such as simulated annealing computationally more reasonable, it is our view that one can often find satisfactory solutions using deterministic optimization algorithms.
1 064 kr
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This volume is a collection of papers on brain mechanisms which integrates theory and experiment to place visual information within the context of the action systems which use it. The book stresses both the intrinsic interest of frog and toad as animals in which to study the neural mechanisms of visuomotor co-ordination and the importance of comparative studies with other organisms. The book demonstrates the interaction between theory and experiment in neuroscience, complementing current data with a rich array of models which together constitute Rana computatrix, the "frog that computes". High-level schema models show the basic functional interactions underlying visuomotor co-ordination, testable by lesion experiments. Neural network models address data from neurophysiology and neuroanatomy. Although the stress in the modeling is on Computational Neuroscience to understand neurobiological phenomena, the results have implications for Neural Engineering, the use of ideas inspired by the study of the brain to design highly parallel, often adaptive, machines.
Neuroscience: From Neural Networks to Artificial Intelligence
Proceedings of a U.S.-Mexico Seminar held in the city of Xalapa in the state of Veracruz on December 9–11, 1991
Häftad, Engelska, 1993
1 096 kr
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The Central Nervous System can be considered as an aggregate of neurons specialized in both the transmission and transfomation of information. Information here has been used for many purposes, but the most important one is probably to generate a representation of the "extenal" world that allows the organism to react properly to changes in its extenal environment. These functions range from such basic ones as detection of changes that may lead to tissue damage and eventual destruction of the organism and the implementation of avoidance reactions to more elaborate representations of the extemal world implying recognition of shapes, sounds and textures as the basis of planned action or even reflection. The question is, how can we hope to understand the complexity inherent in this range of functionalities? One of the distinguishing features of the last two decades has been the availability of computational power that has impacted the many areas of science concerned with this question.An effort has been made within this book to cross boundaries and to have active scientists from different backgrounds and disciplines explain the basic principles which guide their investigations with the hope that this will lay the basis for a future collaborative effort to understand the principles of neural networks.