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Fused deep learning classified early enamel caries with high accuracy
Deep learning framework with quantum-inspired feature fusion achieves 99.33% accuracy for automated enamel caries classification in intraoral photographs with visual explainability.
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Geospatial foundation models improved tree species mapping accuracy
Foundation models outperform conventional satellite methods for tree species classification in mountain forests, achieving high accuracy with minimal training data but requiring nonlinear classifiers.
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Vision–language model improved pediatric dental disease classification
Deep learning vision-language model for diagnosing pediatric dental diseases in panoramic radiographs, combining visual and textual information with 90% accuracy for caries and periapical.
