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Wei Li

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Open access Aug 2026

DAPR: Dynamic Distribution-Aware and Adaptive Pseudo-Label Refinement for Long-Tailed Semi-Supervised Oral Disease Classification

DAPR achieves the highest average Accuracy and Macro-F1 among the compared methods and obtains strong aggregate tail-class performance, particularly for Tooth Discoloration and Ulcers, indicating that DAPR improves aggregate class-balanced learning under the evaluated dataset, annotation ratio, and backbone configuration.

Xuesheng Bian, Zeyu Xie, Yuhan Sun et al. · 0 citations

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