SWIFTT’s findings will be communicated at scientific conferences and published in open-access journals. Find below the current list of publications.

Machine Learning Models and Technology for Classification of Forest on Satellite Data

The paper deals with the problem of semantic segmentation of satellite imagery to deliver forest type map with high resolution. To solve the problem, the researchers propose 4 machine learning models.

Y. Salii, V. Kuzin, A. Hohol, N. Kussul and H. Yailymova, IEEE EUROCON 2023 - 20th International Conference on Smart Technologies, Torino, Italy, 2023, pp. 93-98, doi: 10.1109/EUROCON56442.2023.10199006.

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SILVIA: An eXplainable Framework to Map Bark Beetle Infestation in Sentinel-2 Images

This study explores the achievements of machine learning to perform the inventory mapping of bark beetle infestation hotspots in Sentinel-2 images.

G. Andresini, A. Appice and D. Malerba, in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, doi: 10.1109/JSTARS.2023.3312521.

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