DIATLAS - The French freshwater DIatom ATLAS image dataset
Authors/Creators
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1.
Université de Lorraine
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2.
Laboratoire Interdisciplinaire des Environnements Continentaux
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3.
National Research Institute For Agriculture, Food And Environment
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4.
Luxembourg Institute of Science and Technology
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5.
CentraleSupélec
- 6. Institut National de Recherche pour l'Agriculture l'Alimentation et l'Environnement Nouvelle-Aquitaine Bordeaux Centre
Description
This dataset contains photonic (optical) microscopy images of diatoms extracted from French regional atlases, documenting specimens collected from freshwater streams. These images were acquired using either Bright Field (BF) or Differential Interference Contrast (DIC) techniques. Each image is associated with a taxonomic classification.
This dataset was used to train two Convolutional Neural Network (CNN) models:
- A detection model, based on the ai4oshub/ai4os-yolov8-torch module, designed to predict oriented bounding boxes around diatoms. It is built on a pre-trained YOLOv8, fine-tuned on manually labeled data.
- A classification model, based on Ultralytics' YOLOv8-cls architecture, designed to classify diatom at the species level.
> Diatom classification at the species level
Image metadata are provided in the diatoms.csv, sources.csv, and taxonomic_code.csv files.
Technical info
All informations are detailed in the README.pdf
Data sources
The dataset is based on images gathered from French regional diatom taxonomic atlases (available as open-access PDFs). All informations are detailed in the README.pdf
Contact information
For more information on the dataset and/or the models, you can contact martin.laviale @ univ-lorraine.fr & Jeremy.Fix @ centralesupelec.fr
Files
README.pdf
Files
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Additional details
Additional titles
- Alternative title
- Diatom Atlas Dataset
Related works
- Is new version of
- Dataset: 10.12763/UADENQ (DOI)