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Titlebook: Low-Power Smart Imagers for Vision-Enabled Sensor Networks; Jorge Fernández-Berni,Ricardo Carmona-Galán,ángel Book 2012 Springer Science+

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發(fā)表于 2025-3-21 18:36:22 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Low-Power Smart Imagers for Vision-Enabled Sensor Networks
編輯Jorge Fernández-Berni,Ricardo Carmona-Galán,ángel
視頻videohttp://file.papertrans.cn/589/588897/588897.mp4
概述Describes a system-level approach for designing of vision devices and embedding them into vision-enabled, wireless sensor networks.Surveys state-of-the-art, vision-enabled WSN nodes.Includes details o
圖書(shū)封面Titlebook: Low-Power Smart Imagers for Vision-Enabled Sensor Networks;  Jorge Fernández-Berni,Ricardo Carmona-Galán,ángel  Book 2012 Springer Science+
描述.This book presents a comprehensive, systematic approach to the development of vision system architectures that employ sensory-processing concurrency and parallel processing to meet the autonomy challenges posed by a variety of safety and surveillance applications. ?Coverage includes a thorough analysis of resistive diffusion networks embedded within an image sensor array. This analysis supports a systematic approach to the design of spatial image filters and their implementation as vision chips in CMOS technology. The book also addresses system-level considerations pertaining to the embedding of these vision chips into vision-enabled wireless sensor networks..?Describes a system-level approach for designing of vision devices and ?embedding them into vision-enabled, wireless sensor networks; Surveys state-of-the-art, vision-enabled WSN nodes; Includes details of specifications and challenges of vision-enabled WSNs; Explains architectures for low-energy CMOS vision chips with embedded, programmable spatial filtering capabilities; Includes considerations pertaining to the integration of vision chips into off-the-shelf WSN platforms.
出版日期Book 2012
關(guān)鍵詞Embedded Systems; Low Power Smart Cameras; Low Power Smart Imagers; Smart Cameras; Smart Imagers; Vision
版次1
doihttps://doi.org/10.1007/978-1-4614-2392-8
isbn_softcover978-1-4899-9540-7
isbn_ebook978-1-4614-2392-8
copyrightSpringer Science+Business Media New York 2012
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Vision-enabled WSN Nodes: State of the Art,). Each node, commonly referred to as a ., includes sensing, data processing and communicating components. Its usual workflow consists of sensing data, processing it locally and communicating only the required information resulting from this processing. A remarkable feature is that the exact locatio
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VLSI Implementation of Linear Diffusion,rocessing, is the programmability of its inherent Gaussian filtering. Indeed, the VLSI implementation of user-defined image Gaussian filtering has been already explored in the literature. Most of the approaches reported make use of the ability of CMOS processes to integrate signal processing circuit
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FLIP-Q: A QCIF Resolution Focal-Plane Array for Low-Power Image Processing,ts are images, (ii) medium-level tasks, where inputs are images but outputs are attributes extracted from inputs and (iii) high-level tasks, which perform the cognitive functions associated to vision from the result of low- and medium-level tasks. The most remarkable features of low-level tasks are,
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Jorge Fernández-Berni,Ricardo Carmona-Galán,ángel Rodríguez-Vázquezly with language technology for CH/SSH domains.Unique presen.The digital age has had a profound effect on our cultural heritage and the academic research that studies it. Staggering amounts of objects, many of them of a textual nature, are being digitised to make them more readily accessible to both
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