Monitoring Nests of Solitary Bees using Image Processing Techniques

被引:0
|
作者
Hart, N. H. [1 ]
Huang, L. [1 ]
机构
[1] Auckland Univ Technol, Sch Engn, Auckland, New Zealand
关键词
Image processing; machine vision; data mining; fast random forest; WEKA; FIJI; ecological monitoring; native bees; solitary bees; insects;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The results from monitoring New Zealand's native bees based on image processing techniques are presented. Rather than identifying individual bees directly images of active ground nests are collected, processed and counted. The number of nests is good estimate of population since the number of bees in each nest is constant for most native species; described as solitary because a single female constructs a single nest. Open source software FIJI was used to pre-process and classify images. Accuracies were verified using data mining software WEKA. To date, the random forest classifier has returned fast effective results, classifying nests which are otherwise impossible to identify with the naked eye. Population fluctuations are evident when the two seasons are compared. This method produces repeatable, reliable estimations of the population status of New Zealand native bees.
引用
收藏
页码:1 / 4
页数:4
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