HUNT4 Oral Health Study

A dataset of 13,887 bitewings from the HUNT4 Oral Health Study were annotated individually by six different experts, and used to train three different object detection deep-learning architectures: RetinaNet (ResNet50), YOLOv5 (M size), and EfficientDet (D0 and D1 sizes).

Data and Resources

Cite this as

Javier Pérez de Frutos, Ragnhild Holden Helland, Shreya Desai, Line Cathrine Nymoen, Thomas Langø, Theodor Remman, Abhijit Sen (2024). Dataset: HUNT4 Oral Health Study. https://doi.org/10.57702/tvg7sln2

DOI retrieved: December 16, 2024

Additional Info

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Created December 16, 2024
Last update December 16, 2024
Author Javier Pérez de Frutos
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Ragnhild Holden Helland
Shreya Desai
Line Cathrine Nymoen
Thomas Langø
Theodor Remman
Abhijit Sen