NDLI: Collaborative hybrid classifier learning with ant colony optimization in wireless multimedia sensor networks

Content Provider	IEEE Xplore Digital Library
Author	Sheng Wang Xue Wang Liang Ding Daowei Bi Zheng You
Copyright Year	2008
Description	Author affiliation: Dept. of Precision Instrum., Tsinghua Univ., Beijing (Sheng Wang; Xue Wang; Liang Ding; Daowei Bi; Zheng You)
Abstract	Wireless multimedia sensor network (WMSN) has powerful multimedia signal acquisition and processing abilities. This paper proposes a collaborative hybrid classifier learning algorithm to achieve online support vector machine (SVM) learning for robust target classification in WMSN. The proposed algorithm is carried out in a hybrid computing paradigm, which combines the advantages of progressive computing paradigm and P2P computing paradigm. Importantly, the participant sensor nodes are purposefully selected by evaluating the specific effectiveness. With the sensor nodes selection strategy, the energy consumption and the impact of inevitable missing detection and false detection can be reduced. Besides, ant colony optimization is also used for decreasing the energy consumption in routing. Experimental results demonstrate that the collaborative hybrid classifier learning algorithm can effectively implement target classification in WMSN, and the ant colony optimization based routing and clustering method can largely decrease the energy consumption and time cost.
Starting Page	3341
Ending Page	3346
File Size	696414
Page Count	6
File Format	PDF
ISBN	9781424421138
DOI	10.1109/WCICA.2008.4594495
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Energy consumption Routing Classification algorithms Support vector machines Accuracy Collaboration Feature extraction ant colony optimization Wireless sensor networks target classification collaborative learning support vector machine
Content Type	Text
Resource Type	Article

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