lightbulbPractical problemHAR模型鲁棒性、泛化与数据增强
非专家用户难以灵活定义和调试个性化活动识别规则。UbiComp '24
传感、识别与安全 / HAR模型鲁棒性、泛化与数据增强
非专家用户难以灵活定义和调试个性化活动识别规则。
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lightbulbPractical problemHAR模型鲁棒性、泛化与数据增强
现有方法对IMU数据特征提取效率低，导致活动识别性能受限。UbiComp '24Initial Investigation of Kolmogorov-Arnold Networks (KANs) as Feature Extractors for IMU Based Human Activity Recognition
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智能设备中人类活动识别模型在新场景下经常失效。UbiComp '24
lightbulbPractical problemHAR模型鲁棒性、泛化与数据增强
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lightbulbPractical problemHAR模型鲁棒性、泛化与数据增强
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健康监测等场景中传感器数据丢失导致活动识别效果下降。UbiComp '24Sussex-Huawei Locomotion Recognition Using Machine Learning and Deep Learning with Multi-sensor Data
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用户在传感器数据缺失时无法准确识别活动，影响设备功能。UbiComp '24Ensemble Learning Approach for Human Activity Recognition Involving Missing Sensor Data