Fine Tuning Large Models for Straw Detection in Harvested Fields Under Few-Shot Learning Scenarios
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DOI: 10.1109/lgrs.2025.3548106
Abstract: The effective monitoring of crop residues, particularly straw in non-harvested fields, is essential for sustainable agricultural practices and environmental management. Traditional methods of straw detection often face challenges due to limited training data, high annotation… read more here.
Keywords: learning scenarios; shot learning; straw detection; tuning large ... See more keywords