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Reliability-driven sensor fusion with application in automatic signature verifications.

紀錄類型:	書目-電子資源 : 單行本
正題名/作者:	Reliability-driven sensor fusion with application in automatic signature verifications./
作者:	Alamrony, Naji Emhemed.
面頁冊數:	142 p.
附註:	Source: Masters Abstracts International, Volume: 42-03, page: 1048.
Contained By:	Masters Abstracts International42-03.
標題:	Engineering, System Science. -
電子資源:	Download fulltext (下載全文)
ISBN:	0612850226

Reliability-driven sensor fusion with application in automatic signature verifications.
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100 1 $a Alamrony, Naji Emhemed. $3 1000005699
245 1 0 $a Reliability-driven sensor fusion with application in automatic signature verifications.
300 $a 142 p.
500 $a Source: Masters Abstracts International, Volume: 42-03, page: 1048.
500 $a Advisers: O. A. Basir; G. L. Hayward.
502 $a Thesis (M.Sc.)--University of Guelph (Canada), 2003.
520 $a The reliability of Intelligent Sensory Systems with multi-failure modes is a research area that at the present time lacks adequate attention. In this thesis a novel formulation for assessing and optimizing the reliability of multi sensory systems is proposed. This formulation is capable of modelling a system with m failure modes, under three operational schemes. For each operational scheme an analytical reliability assessment model is developed. Adapting the Voting as a fusion technique, heuristic techniques and genetic algorithms are developed to optimize these models under the different modes of operation. Waveform classification and signature verification problems are used to explain and demonstrate the potential of the proposed formulation.
520 $a Experimental results showed that without optimization the performance of multi-sensor multi-failure mode systems slightly underperformed the performance of some individual sensors. However, the performance of the heuristically optimized versions of these systems outperformed the performance of the best sensor used in such systems. This was true for both waveform classification and signature verification problems. Furthermore, by optimizing signature verification system using genetic algorithms a state-of-the-art performance of 96% was reached.
590 $a School code: 0081.
650 4 $a Engineering, System Science. $3 1000005581
650 4 $a Artificial Intelligence. $3 165300
650 4 $a Engineering, Electronics and Electrical. $3 170927
690 $a 0790
690 $a 0800
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710 2 0 $a University of Guelph (Canada). $3 1000005700
773 0 $t Masters Abstracts International $g 42-03.
790 1 0 $a Basir, O. A., $e advisor
790 1 0 $a Hayward, G. L., $e advisor
790 $a 0081
791 $a M.Sc.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MQ85022 $z Download fulltext (下載全文)