Selected article for: "artificial neural network and test accuracy"
Author: You, Sang-Hee; Hwang, Min; Kim, Ki-Hoon; Cho, Chang-Suk
Title: Development of a Non-contact Autostereoscopic 3D Button Using Artificial Intelligence
  • Cord-id: llmli5ge
  • Document date: 2020_12_17
    • ID: llmli5ge
    Snippet: This study presents the results of the development of a contactless button device that represents the button as an autostereoscopic vision and visually captures the position of the fingertip that presses the virtual button. To this end, a 3D stereoscopic expression module, a pointing location display module, an FPGA design for driving the modules, and an artificial neural network algorithm were developed. The pointing accuracy of the developed button device showed 99% accuracy in the recognition
    Document: This study presents the results of the development of a contactless button device that represents the button as an autostereoscopic vision and visually captures the position of the fingertip that presses the virtual button. To this end, a 3D stereoscopic expression module, a pointing location display module, an FPGA design for driving the modules, and an artificial neural network algorithm were developed. The pointing accuracy of the developed button device showed 99% accuracy in the recognition test in the laboratory.

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