Can You See It?

IF 0.7 Q4 TELECOMMUNICATIONS
HyeokHyen Kwon, C. Tong, H. Haresamudram, Yan Gao, G. Abowd, Nicholas D. Lane, T. Ploetz
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引用次数: 0

Abstract

Today's smartphones and wearable devices come equipped with an array of inertial sensors, along with IMU-based Human Activity Recognition models to monitor everyday activities. However, such models rely on large amounts of annotated training data, which require considerable time and effort for collection. One has to recruit human subjects, define clear protocols for the subjects to follow, and manually annotate the collected data, along with the administrative work that goes into organizing such a recording.
你能看到吗?
如今的智能手机和可穿戴设备都配备了一系列惯性传感器,以及基于imu的人类活动识别模型,以监测日常活动。然而,这样的模型依赖于大量带注释的训练数据,这需要大量的时间和精力来收集。必须招募人类受试者,定义受试者要遵循的明确协议,并手动注释收集到的数据,以及组织此类记录的管理工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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