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Improving Reliability of Magnetic Localization Using Input Space Transformation
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  • Cem Yaldiz ,
  • Nordine Sebkhi ,
  • Arpan Bhavsar ,
  • Jun Wang ,
  • Omer Inan
Cem Yaldiz
Georgia Institute of Technology

Corresponding Author:[email protected]

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Nordine Sebkhi
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Arpan Bhavsar
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Omer Inan
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The distribution shift due to magnetization differences in magnetometers causes machine learning-based magnetic localization models to be ineffective for the end user. We present a novel post-deployment calibration mechanism to mitigate this issue.
2023Published in IEEE Sensors Journal on pages 1-1. 10.1109/JSEN.2023.3320033