센서학회지 (Journal of Sensor Science and Technology)

  • 제30권1호
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  • Pages.1-9
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  • 2021
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  • 1225-5475(pISSN)
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  • 2093-7563(eISSN)
한국센서학회 (The Korean Sensors Society)
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Machine Learning in FET-based Chemical and Biological Sensors: A Mini Review

  • Ahn, Jae-Hyuk (Department of Electronics Engineering, Chungnam National University)
  • 투고 : 2020.12.01
  • 심사 : 2021.01.23
  • 발행 : 2021.01.31
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⟨ 이전 논문 다음 논문 ⟩

초록

This mini review summarizes some of the recent advances in machine-learning (ML)-driven chemical and biological sensors. Specific focus is on field-effect-transistor (FET)-based sensors with a description of their structures and detection mechanisms. Key ML techniques are briefly reviewed for an audience not familiar with the basic principles. We mainly discuss two aspects: (1) data analysis based on ML and (2) ML applied to sensor design. In conclusion, the challenges and opportunities for the advancement of ML-based sensors are briefly considered.

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참고문헌

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