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CROMOSim: A Deep Learning-Based Cross-Modality...
Journal article

CROMOSim: A Deep Learning-Based Cross-Modality Inertial Measurement Simulator

Abstract

With the prevalence of wearable devices, inertial measurement unit (IMU) data has been utilized in monitoring and assessing human mobility such as human activity recognition (HAR) and human pose estimation (HPE). Training deep neural network (DNN) models for these tasks require a large amount of labelled data, which are hard to acquire in uncontrolled environments. To mitigate the data scarcity problem, we design CROMOSim, a cross-modality …

Authors

Hao Y; Lou X; Wang B; Zheng R

Journal

IEEE Transactions on Mobile Computing, Vol. 23, No. 1, pp. 302–312

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

DOI

10.1109/tmc.2022.3230370

ISSN

1536-1233