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Titlebook: Video Image Detection Systems Installation Performance Criteria; Daniel T. Gottuk Book 2008 Fire Protection Research Foundation 2008 IR il

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書目名稱Video Image Detection Systems Installation Performance Criteria
編輯Daniel T. Gottuk
視頻videohttp://file.papertrans.cn/983/982918/982918.mp4
概述Includes supplementary material:
叢書名稱SpringerBriefs in Fire
圖書封面Titlebook: Video Image Detection Systems Installation Performance Criteria;  Daniel T. Gottuk Book 2008 Fire Protection Research Foundation 2008 IR il
描述Computer processing and image analysis technologies have improved substantially over the course of the past decade. This rapidly advancing technology along with the emphasis on video surveillance since 911 has propelled the development of effective video image detection (VID) systems for ?re. Fire protection system designers initially employed these VID systems for use in large facilities, outdoor locations and tunnels. However, video-based detection is being used for a broadening range of applications [e. g. , 1]. For example, these systems are c- rently installed in electrical power plants, paper mills, document storage facilities, historic municipal buildings, nuclear research facilities, automotive plants, wa- house/distribution centers, and onshore and offshore oil platforms. The 2007 edition of NFPA 72, National Fire Alarm Code [2], recognized the use of VID systems for ?ame and smoke detection. Although recognized, there is limited prescriptive installation and use requirements and there is a general desire by many for the development of performance criteria that ultimately could be utilized for the design of systems or the creation of standards. Since the underlying VID tec
出版日期Book 2008
關(guān)鍵詞IR illuminators; camera system; computer vision; detection; smoke detection; video image detection
版次1
doihttps://doi.org/10.1007/978-1-4614-4202-8
isbn_softcover978-1-4614-4201-1
isbn_ebook978-1-4614-4202-8Series ISSN 2193-6595 Series E-ISSN 2193-6609
issn_series 2193-6595
copyrightFire Protection Research Foundation 2008
The information of publication is updating

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978-1-4614-4201-1Fire Protection Research Foundation 2008
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Video Image Detection Systems Installation Performance Criteria978-1-4614-4202-8Series ISSN 2193-6595 Series E-ISSN 2193-6609
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Daniel T. Gottukdeling, Hierarchical ANN, Inference and Recognition, Information and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and Cybersecurity, ML and Social Media, ML in Engineering, Movement and Motion Detecti
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Daniel T. Gottukion. Due to the inherent nature of machine learning and total-order relation, less features are needed to represent data without adverse effecting on performance. Moreover, we propose two efficient methods, namely Adaptive Neighbors Selection(ANS) and Uniform Neighbors Serialization(UNS), to reduce
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