浮游动物
计算机科学
数字图像
浮游生物
人工智能
模式识别(心理学)
图像处理
生态学
图像(数学)
生物
作者
Gaby Gorsky,Mark D. Ohman,Marc Picheral,Stéphane Gasparini,Lars Stemmann,Jean‐Baptiste Romagnan,A Cawood,Stéphane Pesant,Carmen García‐Comas,F. Prejger
出处
期刊:Journal of Plankton Research
[Oxford University Press]
日期:2010-02-04
卷期号:32 (3): 285-303
被引量:415
标识
DOI:10.1093/plankt/fbp124
摘要
ZooScan with ZooProcess and Plankton Identifier (PkID) software is an integrated analysis system for acquisition and classification of digital zooplankton images from preserved zooplankton samples. Zooplankton samples are digitized by the ZooScan and processed by ZooProcess and PkID in order to detect, enumerate, measure and classify the digitized objects. Here we present a semi-automatic approach that entails automated classification of images followed by manual validation, which allows rapid and accurate classification of zooplankton and abiotic objects. We demonstrate this approach with a biweekly zooplankton time series from the Bay of Villefranche-sur-mer, France. The classification approach proposed here provides a practical compromise between a fully automatic method with varying degrees of bias and a manual but accurate classification of zooplankton. We also evaluate the appropriate number of images to include in digital learning sets and compare the accuracy of six classification algorithms. We evaluate the accuracy of the ZooScan for automated measurements of body size and present relationships between machine measures of size and C and N content of selected zooplankton taxa. We demonstrate that the ZooScan system can produce useful measures of zooplankton abundance, biomass and size spectra, for a variety of ecological studies.
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