What makes this research particularly compelling is the convergence of three powerful ideas that are rarely combined in a single experimental study: continuous wavelet transform (CWT) scalogram image generation, masked autoencoder (MAE) self-supervised The paper addresses the high computational cost of active learning, where large models must be repeatedly trained to select informative data for labeling. This limits its practicality, especially for large-scale or resource-c