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Article

MorphoCluster: Efficient Annotation of Plankton Images by Clustering

1
Department of Computer Science, Kiel University, 24118 Kiel, Germany
2
Laboratoire d’Océanographie de Villefranche-sur-mer, 06230 Villefranche-sur-Mer, France
3
GEOMAR Helmholtz Center for Ocean Research Kiel, 24148 Kiel, Germany
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(11), 3060; https://doi.org/10.3390/s20113060
Received: 30 April 2020 / Revised: 22 May 2020 / Accepted: 25 May 2020 / Published: 28 May 2020
(This article belongs to the Special Issue Sensor Applications on Marine Recognition)
In this work, we present MorphoCluster, a software tool for data-driven, fast, and accurate annotation of large image data sets. While already having surpassed the annotation rate of human experts, volume and complexity of marine data will continue to increase in the coming years. Still, this data requires interpretation. MorphoCluster augments the human ability to discover patterns and perform object classification in large amounts of data by embedding unsupervised clustering in an interactive process. By aggregating similar images into clusters, our novel approach to image annotation increases consistency, multiplies the throughput of an annotator, and allows experts to adapt the granularity of their sorting scheme to the structure in the data. By sorting a set of 1.2 M objects into 280 data-driven classes in 71 h (16 k objects per hour), with 90% of these classes having a precision of 0.889 or higher. This shows that MorphoCluster is at the same time fast, accurate, and consistent; provides a fine-grained and data-driven classification; and enables novelty detection. View Full-Text
Keywords: machine learning; deep learning; clustering; plankton image classification; marine image recognition; marine image annotation machine learning; deep learning; clustering; plankton image classification; marine image recognition; marine image annotation
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MDPI and ACS Style

Schröder, S.-M.; Kiko, R.; Koch, R. MorphoCluster: Efficient Annotation of Plankton Images by Clustering. Sensors 2020, 20, 3060. https://doi.org/10.3390/s20113060

AMA Style

Schröder S-M, Kiko R, Koch R. MorphoCluster: Efficient Annotation of Plankton Images by Clustering. Sensors. 2020; 20(11):3060. https://doi.org/10.3390/s20113060

Chicago/Turabian Style

Schröder, Simon-Martin, Rainer Kiko, and Reinhard Koch. 2020. "MorphoCluster: Efficient Annotation of Plankton Images by Clustering" Sensors 20, no. 11: 3060. https://doi.org/10.3390/s20113060

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