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Generating high-quality synthetic samples for minority classes can dramatically enhance classifier performance in imbalanced time-series tasks.
UAV-MapFusion achieves unprecedented mapping accuracy by effectively aligning multi-session point clouds while mitigating drift, even under challenging conditions.
Genetic programming can automatically discover lightweight, generalizable feature extractors for time series classification that outperform standard methods.
