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.
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页码：45 / 55
页数：11
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