Fig. 17
From: Rayleigh-wave dispersion data selection and model fine-tuning based on uncertainty estimation
Comparison of model predictions obtained under different training data sizes and refinement strategies. The result reveals a critical insight: scaling up synthetic data alone is an inefficient strategy for improving field data performance. Even when the synthetic training set is doubled, its performance on field data is markedly inferior to that of a model fine-tuned with only 36 samples using our method. This comparison clearly demonstrates the superiority of our targeted fine-tuning strategy over the conventional approach of merely expanding synthetic data volume.
