Explainable few-shot learning workflow for detecting invasive and exotic tree species

Explainable few-shot learning workflow for detecting invasive and exotic tree species

Abstract Deep Learning methods are notorious for relying on extensive labeled datasets to train and assess their performance. This can cause difficulties in practical situations where models should be trained for new applications for which very little data is available. While few-shot learning algor...

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Bibliographic Details
Main Authors: Caroline M. Gevaert, Alexandra Aguiar Pedro, Ou Ku, Hao Cheng, Pranav Chandramouli, Farzaneh Dadrass Javan, Francesco Nattino, Sonja Georgievska
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Explainable AI
Few-shot learning
Forestry
Object detection
Unmanned aerial vehicles
Siamese networks
Online Access:https://doi.org/10.1038/s41598-025-05394-2
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https://doi.org/10.1038/s41598-025-05394-2

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