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  • 8/6/2019 An Application of Ant Colony Algorithm for Edge Feature Extraction in City Aerial Image for Building Recognition

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    An Application of Ant Colony Algorithm for Edge

    Feature Extraction in City Aerial Image forBuilding Recognition

    Guo Yurong; Wei Zhenzhong; Zhang Guangjun;

    Electronic Measurement and Instruments, 2007. ICEMI '07. 8th International Conference onDigital Object Identifier: 10.1109/ICEMI.2007.4350837Publication Year: 2007 , Page(s): 2-944 - 2-947

    The Improvement of Ant Colony Algorithm and ItsApplication to TSP Problem

    Jin Zhang; Huaishan Liu; Siyou Tong; Ling Wang;Wireless Communications, Networking and Mobile Computing, 2009. WiCom '09. 5thInternational Conference onDigital Object Identifier: 10.1109/WICOM.2009.5301753Publication Year: 2009 , Page(s): 1 - 4

    Design and Implementation of a Fuzzy-ModifiedAnt Colony Hardware Structure for ImageRetrieval

    Konstantinidis, K.; Sirakoulis, G.C.; Andreadis, I.;Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions onVolume: 39 , Issue: 5Digital Object Identifier: 10.1109/TSMCC.2009.2020511Publication Year: 2009 , Page(s): 520 - 533

    IEEE JOURNALS

    Abstract | Full Text: PDF (993 KB)

    Ant Colony Optimization Algorithm for Fuzzy Controller Design and Its FPGAImplementation

    Chia-Feng Juang; Chun-Ming Lu; Chiang Lo; Chi-Yen Wang;Industrial Electronics, IEEE Transactions onVolume: 55 , Issue: 3Digital Object Identifier: 10.1109/TIE.2007.909762Publication Year: 2008 , Page(s): 1453 - 1462

    IEEE JOURNALS

    Abstract | Full Text: PDF (612 KB)

    Design of intelligent mobile vehicle system and itsglobal optimal path planning

    Xiaoyong Ye; Yong Lei; Haijun Hou;Industrial Technology, 2008. ICIT 2008. IEEE International Conference onDigital Object Identifier: 10.1109/ICIT.2008.4608359Publication Year: 2008 , Page(s): 1 - 5

    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  • 8/6/2019 An Application of Ant Colony Algorithm for Edge Feature Extraction in City Aerial Image for Building Recognition

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    IEEE CONFERENCES

    Abstract | Full Text: PDF (123 KB)

    The intelligent mobile vehicle (IMV) is designed on embedded system with ARM9 and WindowsCE.NET embedded operation system (EOS). It is a completely autonomous mobile vehicle systemwith hardware executive mechanics and corresponding intelligent path planning algorithm. Thegoal for the IMV is to run from the start point to the end point along the shortest path in anyrandom scene autonomously. There are three problems needed to be solved to fulfill the goal:acquire the scene information, quickly plan out the global shortest path and track the optimalpath. The global scene information is got through camera on top, then processed andtransmitted to the IMV by radio and the global optimal path is planned out based on improvedant colonyalgorithm. The IMV tracks the optimal path by controlling the driver wheels with twoDC motors based on fuzzy control method. Many sensors also must be equipped to assisttracking the shortest path. All the algorithms are realized with C++ under Windows CE.NET. Theexperiments show that the IMV system has a good performance in planning and tracking theglobal optimal path autonomously. Read More

    An Ant based simulation optimization for Vehicle Routing Problem withstochastic demands

    Tripathi, M.; Kuriger, G.; Hung-da Wan;Winter Simulation Conference (WSC), Proceedings of the 2009Digital Object Identifier: 10.1109/WSC.2009.5429417Publication Year: 2009 , Page(s): 2476 - 2487

    IEEE CONFERENCES

    Abstract | Full Text: PDF (960 KB)

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