lightbulb现实痛点HAR模型鲁棒性、泛化与数据增强
真实场景中传感器数据常有丢失，活动识别模型准确率低。UbiComp '22Augmented Adversarial Learning for Human Activity Recognition with Partial Sensor Sets
传感、识别与安全 / HAR模型鲁棒性、泛化与数据增强
真实场景中传感器数据常有丢失，活动识别模型准确率低。
同类问题
lightbulb现实痛点HAR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
lightbulb现实痛点HAR模型鲁棒性、泛化与数据增强
智能设备中人类活动识别模型在新场景下经常失效。UbiComp '24
lightbulb现实痛点HAR模型鲁棒性、泛化与数据增强
现有的人体活动识别技术易受环境影响且能耗较高。UbiComp '24Body-Centric Capacitance or Electric Field Sensing for Human Activity Recognition and Human-Computer Interaction: A Comprehensive Review
lightbulb现实痛点HAR模型鲁棒性、泛化与数据增强
现有算法难以在真实复杂环境中准确识别人类活动。UbiComp '2412th International Workshop on Human Activity Sensing Corpus and Applications (HASCA)
lightbulb现实痛点HAR模型鲁棒性、泛化与数据增强
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
lightbulb现实痛点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。UbiComp '24