AUTOMATIC FISH POPULATION COUNTING BY ARTIFICIAL NEURAL-NETWORK

被引：34

作者：

NEWBURY, PF

CULVERHOUSE, PF

PILGRIM, DA

机构：

[1] UNIV PLYMOUTH,SCH ELECTR COMMUNICAT & ELECT ENGN,CTR INTELLIGENT SYST,PLYMOUTH PL4 8AA,DEVON,ENGLAND

[2] UNIV PLYMOUTH,INST MARINE STUDIES,PLYMOUTH PL4 8AA,DEVON,ENGLAND

来源：

AQUACULTURE | 1995年 / 133卷 / 01期

关键词：

ARTIFICIAL NEURAL NETWORK; POPULATION COUNTING; FISH;

D O I：

10.1016/0044-8486(95)00003-K

中图分类号：

S9 [水产、渔业];

学科分类号：

0908 ;

摘要：

A new method of automatically counting fish using an artificial neural network is presented. A back propagation of error feed-forward neural network has been trained to count synthetic fish populations. Trained networks are subsequently shown to generalise well to previously unseen fish tank scenes, giving a 94% success rate on scenes containing up to 100 fish in a variety of orientations and overlaps. This out-performs both pixel counting and energy estimation methods.

引用

页码：45 / 55

页数：11

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