Data augmentation for pathogen segmentation in vinewood fluorescence microscopy images
Résumé
In this paper, we address the problem of segmentation of vine pathogens within fluorescence microscopy images. To our knowledge, the quantification from such images is an original problem. As a consequence, there is no available database to rely upon in order to use supervised machine learning techniques. We provide a workaround by creating realistic images containing the desired filamentary pattern and variable blur effect. Numerical results show the interest of this data augmentation technique, especially on images corresponding to difficult segmentation.
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Cite 10.24432/C5WK7G Jeu de données Julie Munsch, S. O. (2024). An eye on the vine - a dataset for fungi segmentation in microscopic vine wood images [Data set]. UCI Machine Learning Repository. https://doi.org/10.24432/C5WK7G