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Using Echo Ultrasound from Schooling Fish to Detect and Classify Fish Types

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摘要 Fishfindershavealreadybeenwidelyavailableinthefishingmarketforanumberofyears.However,thesizesofthesefishfindersaretoobigandtheirpricesareexpensivetosuitfortheresearchofroboticfishormini-submarine.Thegoalofthisresearchistoproposealow-costfishdetectorandclassifierwhichsuitsforunderwaterrobotorsubmarineasaproximitysensor.Withsomepre-conditioninhardwareandalgorithms,theexperimentalresultsshowthattheproposeddesignhasgoodper-formance,withadetectionrateof100%andaclassificationrateof94%.Boththeexistingtypeoffishandthegroupbehaviorcanberevealedbystatisticalinterpretationssuchashoveringpassionandsparseswimmingmode.

DOI mpj0n5684y/124675

作者 Yeffry Handoko;Yul.Y.Nazaruddin;Huosheng Hu

机构地区不详

出处《仿生工程学报：英文版》 2009年3期

关键词 FISH detection classincation artificial NEURAL network

分类 [生物学][生物工程]

出版日期 2009年03月13日（中国期刊网平台首次上网日期，不代表论文的发表时间）

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来源期刊

仿生工程学报：英文版

2009年3期

Using Echo Ultrasound from Schooling Fish to Detect and Classify Fish Types

来源期刊

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Using Echo Ultrasound from Schooling Fish to Detect and Classify Fish Types

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