Articles | Volume 39, issue 2
https://doi.org/10.5194/jm-39-183-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/jm-39-183-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Automated analysis of foraminifera fossil records by image classification using a convolutional neural network
Aix-Marseille Université, CNRS, IRD, Coll. De France, INRAE, CEREGE, Technopôle de l'Arbois-Méditerranée, Aix-en-Provence, 13545, France
School of Electrical Engineering & Robotics, Queensland University of Technology, Brisbane, Australia
Martin Tetard
Aix-Marseille Université, CNRS, IRD, Coll. De France, INRAE, CEREGE, Technopôle de l'Arbois-Méditerranée, Aix-en-Provence, 13545, France
Adnya Pratiwi
Aix-Marseille Université, CNRS, IRD, Coll. De France, INRAE, CEREGE, Technopôle de l'Arbois-Méditerranée, Aix-en-Provence, 13545, France
Michael Adebayo
Aix-Marseille Université, CNRS, IRD, Coll. De France, INRAE, CEREGE, Technopôle de l'Arbois-Méditerranée, Aix-en-Provence, 13545, France
Thibault de Garidel-Thoron
Aix-Marseille Université, CNRS, IRD, Coll. De France, INRAE, CEREGE, Technopôle de l'Arbois-Méditerranée, Aix-en-Provence, 13545, France
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Cited
41 citations as recorded by crossref.
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- A NEW MODEL ON BENTHIC FORAMINIFER IMAGE CLASSIFICATION AND DEFINITIONS BASED ON CONVENTIONAL NEURAL NETWORK (CNN) K. YAYAN & U. YAYAN 10.31796/ogummf.1096951
- Foram3D: A pipeline for 3D synthetic data generation and rendering of foraminifera for image analysis and reconstruction S. Banerjee et al. 10.1016/j.marmicro.2025.102486
- Environmental Controls of Size Distribution of Modern Planktonic Foraminifera in the Tropical Indian Ocean M. Adebayo et al. 10.1029/2022GC010586
- Temporal changes in zooplankton indicators highlight a bottom-up process in the Bay of Marseille (NW Mediterranean Sea) T. Garcia et al. 10.1371/journal.pone.0292536
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- Machine Learning Classification of Fossilized Pectinodon bakkeri Teeth Images: Insights into Troodontid Theropod Dinosaur Morphology J. Bahn et al. 10.3390/make7020045
- The exploration of the transfer learning technique for Globotruncanita genus against the limited low-cost light microscope images I. Ozer et al. 10.1007/s11760-024-03322-x
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- Deep learning approaches to the phylogenetic placement of extinct pollen morphotypes M. Adaïmé et al. 10.1093/pnasnexus/pgad419
- Enhanced taxonomic identification of fusulinid fossils through image–text integration using transformer F. Zhang et al. 10.1016/j.cageo.2024.105701
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Latest update: 08 Oct 2025
Short summary
Foraminifera are marine microorganisms with a calcium carbonate shell. Their fossil remains build up on the seafloor, forming kilometres of sediment over time. From analysis of the foraminiferal record we can estimate past climate conditions and the geological history of the Earth. We have developed an artificial intelligence system for automatically identifying foraminifera species, replacing the time-consuming manual approach and thus helping to make these analyses more efficient and accurate.
Foraminifera are marine microorganisms with a calcium carbonate shell. Their fossil remains...