Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 18, issue 2
Articles | Volume 18, issue 2
https://doi.org/10.5194/essd-18-945-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-945-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 2
Review article
 | 
05 Feb 2026
Review article |  | 05 Feb 2026

Benchmark of plankton images classification: emphasizing features extraction over classifier complexity

Thelma Panaïotis, Emma Amblard, Guillaume Boniface-Chang, Gabriel Dulac-Arnold, Benjamin Woodward, and Jean-Olivier Irisson

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Short summary
To address the lack of performance benchmark in plankton image classification, we evaluated machine learning methods on six large and realistic datasets. Testing both traditional and more recent convolutional neural networks (deep learning), we find that relatively small deep networks performed best, particularly for uncommon classes, because they extract richer features. Our results indicate that such compact models are sufficient for classifying small grayscale plankton images.
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