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.
· Electronics · 0 citations