Assessment of ZooImage as a tool for the classification of zooplankton
ZooImage, image analysis software, was evaluated to determine its ability to differentiate between zooplankton groups in preserved zooplankton samples collected in Prince William Sound, Alaska. A training set of 53 categories were established to train the software for automatic recognition. Using th...
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2008
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fthighwire:oai:open-archive.highwire.org:plankt:30/12/1351 2023-05-15T18:48:56+02:00 Assessment of ZooImage as a tool for the classification of zooplankton Bell, Jenefer L. Hopcroft, Russell R. 2008-12-01 00:00:00.0 text/html http://plankt.oxfordjournals.org/cgi/content/short/30/12/1351 https://doi.org/10.1093/plankt/fbn092 en eng Oxford University Press http://plankt.oxfordjournals.org/cgi/content/short/30/12/1351 http://dx.doi.org/10.1093/plankt/fbn092 Copyright (C) 2008, Oxford University Press ORIGINAL ARTICLES TEXT 2008 fthighwire https://doi.org/10.1093/plankt/fbn092 2013-05-26T18:07:34Z ZooImage, image analysis software, was evaluated to determine its ability to differentiate between zooplankton groups in preserved zooplankton samples collected in Prince William Sound, Alaska. A training set of 53 categories were established to train the software for automatic recognition. Using the Random forest algorithm, ZooImage identified particles in the training set with less than 13% error. Despite reasonable results with the training set, however, ZooImage was less effective when this training set was used to identify particles from field-collected zooplankton samples. When all particles were examined, ZooImage had an accuracy of 81.7% but this dropped to 63.3% when discard particles (e.g. marine snow and fibers) were removed from total particles. Copepods, the numerically dominant organisms in most samples, were examined separately and were correctly identified 67.8% of the time. Further investigation suggested size was effective in determining identifications; medium size copepods (e.g. Pseudocalanus sp., Acartia sp.) were accurately identified 73.3% of the time. ZooImage can provide a coarse level of taxonomic classification and we anticipate continued improvement to this software should further enhance automatic identification of preserved zooplankton samples. Text Alaska Copepods HighWire Press (Stanford University) Journal of Plankton Research 30 12 1351 1367 |
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HighWire Press (Stanford University) |
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English |
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ORIGINAL ARTICLES |
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ORIGINAL ARTICLES Bell, Jenefer L. Hopcroft, Russell R. Assessment of ZooImage as a tool for the classification of zooplankton |
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ORIGINAL ARTICLES |
description |
ZooImage, image analysis software, was evaluated to determine its ability to differentiate between zooplankton groups in preserved zooplankton samples collected in Prince William Sound, Alaska. A training set of 53 categories were established to train the software for automatic recognition. Using the Random forest algorithm, ZooImage identified particles in the training set with less than 13% error. Despite reasonable results with the training set, however, ZooImage was less effective when this training set was used to identify particles from field-collected zooplankton samples. When all particles were examined, ZooImage had an accuracy of 81.7% but this dropped to 63.3% when discard particles (e.g. marine snow and fibers) were removed from total particles. Copepods, the numerically dominant organisms in most samples, were examined separately and were correctly identified 67.8% of the time. Further investigation suggested size was effective in determining identifications; medium size copepods (e.g. Pseudocalanus sp., Acartia sp.) were accurately identified 73.3% of the time. ZooImage can provide a coarse level of taxonomic classification and we anticipate continued improvement to this software should further enhance automatic identification of preserved zooplankton samples. |
format |
Text |
author |
Bell, Jenefer L. Hopcroft, Russell R. |
author_facet |
Bell, Jenefer L. Hopcroft, Russell R. |
author_sort |
Bell, Jenefer L. |
title |
Assessment of ZooImage as a tool for the classification of zooplankton |
title_short |
Assessment of ZooImage as a tool for the classification of zooplankton |
title_full |
Assessment of ZooImage as a tool for the classification of zooplankton |
title_fullStr |
Assessment of ZooImage as a tool for the classification of zooplankton |
title_full_unstemmed |
Assessment of ZooImage as a tool for the classification of zooplankton |
title_sort |
assessment of zooimage as a tool for the classification of zooplankton |
publisher |
Oxford University Press |
publishDate |
2008 |
url |
http://plankt.oxfordjournals.org/cgi/content/short/30/12/1351 https://doi.org/10.1093/plankt/fbn092 |
genre |
Alaska Copepods |
genre_facet |
Alaska Copepods |
op_relation |
http://plankt.oxfordjournals.org/cgi/content/short/30/12/1351 http://dx.doi.org/10.1093/plankt/fbn092 |
op_rights |
Copyright (C) 2008, Oxford University Press |
op_doi |
https://doi.org/10.1093/plankt/fbn092 |
container_title |
Journal of Plankton Research |
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30 |
container_issue |
12 |
container_start_page |
1351 |
op_container_end_page |
1367 |
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1766242304578813952 |