helpResearch questionHAR模型鲁棒性、泛化与数据增强
语义范围（Activity Semantic Range）和大间隔损失（Large Margin Loss）能否提升模型的分类鲁棒性和准确性？UbiComp '22Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognition
传感、识别与安全 / HAR模型鲁棒性、泛化与数据增强
语义范围（Activity Semantic Range）和大间隔损失（Large Margin Loss）能否提升模型的分类鲁棒性和准确性？
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