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https://doi.org/10.5281/zenodo...
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Dynamic Optimization Cycle (DOC) for Plankton Classification

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 28 Feb 2022 English Publisher:ZenodoFunded by:EC | COMFORT
Authors: Conradt, Jan; Börner, Gregor; Lopez-Urrutia, Ángel; Möllmann, Christian; Moyano, Marta;

doi: 10.5281/zenodo.6303679 , 10.5281/zenodo.6303678

Dynamic Optimization Cycle (DOC) for Plankton Classification

Abstract

This is the application “Dynamic Optimization Cycle (DOC)” for classifying plankton images. The baseline training set is included. The paper introducing the DOC pipeline and -application is currently in final validation for publication in Frontiers in Marine Science (Conradt et al., Automated Plankton Classification with a Dynamic Optimization and Adaptation Cycle). An instruction manual for the usage of the application will be included in the supplementary material of the publication.

Programmed for Linux

Related Organizations
Keywords

Plankton classification, Deep Neural Networks, Model adaptation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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European Marine Science
FORTHEM Alliance
Knowmad Institut
UArctic