Towards a Modular Machine Learning Architecture for Human Activity Recognition

Author:

Schroth Marc1,Birkenmaier Dennis1,Stork Wilhelm2

Affiliation:

1. FZI Research Center for Information Technology,Dept. of Embedded Systems and Sensors Engineering,Karlsruhe,Germany

2. Institute of Information Processing Technologies, Karlsruhe Institute of Technology KIT,Karlsruhe,Germany

Publisher

IEEE

Reference15 articles.

1. United Nations, Department of Economic and Social Affairs, Population Division;World Population Prospects 2022: Summary of Results. UN DESA/POP/2022/TRlNO. 3,2022

2. A Review of Human Activity Recognition Methods

3. Different approaches for human activity recognition: A survey;Zawar;arXiv preprint,2019

4. Human Activity Recognition Using Deep Learning: A Sur-vey;Marutirao Nanche;International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT),2023

5. Worker Activity Recognition in Smart Manufacturing Using IMU and sEMG Signals with Convolutional Neural Networks

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