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Titlebook: Neural Networks for Vision, Speech and Natural Language; R. Linggard (Professor),D. J. Myers,C. Nightingale Book 1992 Springer Science+Bus

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书目名称Neural Networks for Vision, Speech and Natural Language
编辑R. Linggard (Professor),D. J. Myers,C. Nightingale
视频video
丛书名称BT Telecommunications Series
图书封面Titlebook: Neural Networks for Vision, Speech and Natural Language;  R. Linggard (Professor),D. J. Myers,C. Nightingale Book 1992 Springer Science+Bus
描述This book is a collection of chapters describing work carried out as part of a large project at BT Laboratories to study the application of connectionist methods to problems in vision, speech and natural language processing. Also, since the theoretical formulation and the hardware realization of neural networks are significant tasks in themselves, these problems too were addressed. The book, therefore, is divided into five Parts, reporting results in vision, speech, natural language, hardware implementation and network architectures. The three editors of this book have, at one time or another, been involved in planning and running the connectionist project. From the outset, we were concerned to involve the academic community as widely as possible, and consequently, in its first year, over thirty university research groups were funded for small scale studies on the various topics. Co-ordinating such a widely spread project was no small task, and in order to concentrate minds and resources, sets of test problems were devised which were typical of the application areas and were difficult enough to be worthy of study. These are described in the text, and constitute one of the successes
出版日期Book 1992
关键词cognition; detection; image processing; natural language; natural language processing; neural networks; sp
版次1
doihttps://doi.org/10.1007/978-94-011-2360-0
isbn_softcover978-94-010-5041-8
isbn_ebook978-94-011-2360-0
copyrightSpringer Science+Business Media Dordrecht 1992
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Image Feature Location in Multi-Resolution Images Using a Hierarchy of Multilayer Perceptronse and track features in digital image sequences. We have concentrated on the location of eyes and mouths in human head-and-shoulders images, as described by Nightingale in the introduction to this part of the book. However the techniques described should be applicable to determining the position of localised features in general images.
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Finite Wordlength, Integer Arithmetic Multilayer Perceptron Modelling for Hardware Realizationan analogue implementation is being contemplated, it is necessary to know whether the inherent dynamic range and accuracy achievable with the components being used (e.g. resistor or capacitor values) will be adequate to achieve the desired performance of the net.
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The Detection of Eyes in Facial Images Using Radial Basis FunctionsThis chapter describes work done by the authors on the problem of locating eyes in human head and shoulders images, as described in the introduction to Part 1 of this book, and in Chapters 1 and 2.
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Training and Testing of Neural Net Window Operators on Spatiotemporal Image SequencesThe purpose of the investigation was, first, to analyse the ability of single layer neural network algorithms to learn aspects of the local image structure from image sequence data, and second, to test trained networks for their image processing and noise suppression capabilities.
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