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A Dynamic Gesture Recognition Algorithm Using Single Halide Perovskite Photovoltaic Cell for Human-Machine Interaction

  • Kyung-Chan An*
  • , Jun-Ying Li
  • , Chu-Feng Yang
  • , Si En Timothy Ng
  • , Shibi Varku
  • , Qinjie Wu
  • , Priyanka Kajal
  • , Nripan Mathews
  • , Arindam Basu
  • , Tony Tae-Hyoung Kim
  • *Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

This work presents a hand gesture recognition system for a single photovoltaic(PV) cell and provides a comparison and insight into several gesture recognition algorithms. The photovoltaic cell based on halide perovskites is used for a single sensor for hand gesture recognition. The multi-layer perceptron(MLP) classification algorithm was selected to recognize hand gestures from a PV cell after testing and comparing different algorithms. Using the proposed MLP classification algorithm, our proposed hand-gesture recognition system can provide 100% accuracy on our collected dataset. ©2024 IEEE.
Original languageEnglish
Title of host publication2024 International Conference on Electronics, Information, and Communication (ICEIC)
PublisherIEEE
ISBN (Electronic)979-8-3503-7188-8
ISBN (Print)979-8-3503-7189-5
DOIs
Publication statusPublished - 2024
Event23rd International Conference on Electronics, Information, and Communication (ICEIC 2024) - Taipei, Taiwan, China
Duration: 28 Jan 202431 Jan 2024
https://iceic.org/2024/
https://ieeexplore.ieee.org/xpl/conhome/10457047/proceeding

Publication series

NameInternational Conference on Electronics, Information and Communications
ISSN (Print)2574-1403
ISSN (Electronic)2767-7699

Conference

Conference23rd International Conference on Electronics, Information, and Communication (ICEIC 2024)
PlaceTaiwan, China
CityTaipei
Period28/01/2431/01/24
Internet address

Bibliographical note

Research Unit(s) information for this publication is provided by the author(s) concerned.

Funding

An Kyung-Chan and Li Jun-Ying have contributed equally. This research is supported by the National Research Foundation (NRF), Singapore, under its Competitive Research Program (CRP) (NRF-CRP25- 2020-0002).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Research Keywords

  • hand gesture
  • single sensor
  • multi-layer perceptron

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