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Titlebook: Image Processing using Pulse-Coupled Neural Networks; Thomas Lindblad,Jason M. Kinser Book 19981st edition Springer-Verlag London 1998 cog

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發(fā)表于 2025-3-21 17:15:34 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Image Processing using Pulse-Coupled Neural Networks
編輯Thomas Lindblad,Jason M. Kinser
視頻videohttp://file.papertrans.cn/462/461453/461453.mp4
概述PCNN‘s (Pulse-Coupled Neural Networks) are a new and exciting development in image processing research - there are currently no books available on this topic * PCNN research is particularly relevant t
叢書名稱Perspectives in Neural Computing
圖書封面Titlebook: Image Processing using Pulse-Coupled Neural Networks;  Thomas Lindblad,Jason M. Kinser Book 19981st edition Springer-Verlag London 1998 cog
描述Pulse-coupled neural networks represent a new and exciting advance in image processing research. When exposed to grey scale or colour images they produce a series of binary pulse images which allow the content of the image to be assessed much more accurately than from the original. In this volume Thomas Lindblad and Jason Kinser provide a much needed introduction to the topic of PCNNs. They review the theoretical foundations, and then look at a number of image processing applications including segmentation, edge extraction, texture extraction, object identification, object isolation, motion processing, foveation, noise suppression and image fusion. They also look at the PCNNs ability to process logical arguments and at how to implement it in specialised hardware. It will be of particular interest to researchers and practitioners working in image processing, especially those involved with medical, military or industrial applications. It will also be of interest to graduate-level students.
出版日期Book 19981st edition
關(guān)鍵詞cognition; image processing; kernel; neural networks
版次1
doihttps://doi.org/10.1007/978-1-4471-3617-0
isbn_ebook978-1-4471-3617-0Series ISSN 1431-6854
issn_series 1431-6854
copyrightSpringer-Verlag London 1998
The information of publication is updating

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發(fā)表于 2025-3-21 21:21:56 | 只看該作者
Introduction and Theory,tion ability also holds true for animals, to a greater or lesser extent. A spider has no problem recognising a fly. Even a baby spider can do that. At this level we are talking about a few hundred to a thousand processing elements or neurons. Nevertheless the biological systems seem to do their job very well.
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1431-6854 ble on this topic * PCNN research is particularly relevant tPulse-coupled neural networks represent a new and exciting advance in image processing research. When exposed to grey scale or colour images they produce a series of binary pulse images which allow the content of the image to be assessed mu
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Software and Hardware Realisation, very fast. On a 90 MHz Pentium a single PCNN iteration for a 128x128 image takes about one second. While this may be sufficient in many cases, it is not fast enough for real-time applications. Therefore, implementation in parallel computers, dedicated hardware and optical computers are also discussed.
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發(fā)表于 2025-3-22 13:15:48 | 只看該作者
Book 19981st editionuce a series of binary pulse images which allow the content of the image to be assessed much more accurately than from the original. In this volume Thomas Lindblad and Jason Kinser provide a much needed introduction to the topic of PCNNs. They review the theoretical foundations, and then look at a n
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Introduction and Theory,m and was asked to find the light switch it would not take more than a second or two. Even if the light switch was located in a different place than the human expected or it was shaped differently than the human expected it would not be difficult to find the switch. Another example is that of recogn
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Target Recognition,esented in a variety of different views, rotations, scales, illumination, etc. Traditional target recognition methods have been successful only in limited cases and views. However, the three basic steps to Automatic Target Recognition or ATR are well known: (i) segment the image into regions, (ii) d
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