Efficient Deep Learning Adaptation for Cross-Environment RSS-Based Indoor Localization
Experimental results demonstrate that the proposed training strategy enables faster convergence and improved adaptation compared with training from scratch, and reduces training time under different dataset configurations, verifying its effectiveness and efficiency for adaptive RSS-based indoor localization.