Feature fusion algorithm based on modular scalable integrated sensor behavior recognition

Authors

  • Fuyin Wei Fakultät für Ingenieurwissenschaften,Institut für Produkt Engineering, Universität Duisburg-Essen (UDE)
  • Fei Xiang Fakultät für Ingenieurwissenschaften,Institut für Produkt Engineering, Universität Duisburg-Essen (UDE)
  • Bohao Chu Fakultät für Ingenieurwissenschaften,Institut für Produkt Engineering, Universität Duisburg-Essen (UDE)
  • Bernd Noche Fakultät für Ingenieurwissenschaften,Institut für Produkt Engineering, Universität Duisburg-Essen (UDE)

DOI:

https://doi.org/10.2195/lj_Proc_wei_en_202112_01

Keywords:

Convolutional Neural Network, Feature-Fusion, Genauigkeit, Robustheit, accuracy, feature fusion, modular scalable integrated sensor, modularer skalierbarer integrierter Sensor, robustness

Abstract

Based on the behavior recognition model of Convolutional Neural Network, we developed a modular scalable integrated (MSI) sensor system together with a signal feature fusion algorithm. The integrated sensor system can obtain high-quality signals without having to be embedded in the body of the object and has good modular scalability and timeliness. The feature fusion algorithm improves the recognition accuracy as well as the robustness of the model.

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Published

2021-12-13

How to Cite

Wei, F., Xiang, F., Chu, B., & Noche, B. (2021). Feature fusion algorithm based on modular scalable integrated sensor behavior recognition. Logistics Journal: Proceedings, (17). https://doi.org/10.2195/lj_Proc_wei_en_202112_01

Issue

No. 17 (2021): Logistics Journal: Proceedings

Section

Artikel

License

Copyright (c) 2021 Fuyin Wei, Fei Xiang, Bohao Chu, Bernd Noche