Neural network-based touch input classification

Examples are disclosed that relate to improving speed and accuracy of touch input classification. In one example, a touch detection device includes an array of antennas configured to measure touch input and output a touch matrix of pixels having touch values corresponding to the touch input measured...

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Bibliographic Details
Main Authors Tsvetov, Anatoly, Ben-Amram, Nadav Shlomo, Hakim, Adam, Einhoren, Yoel Yehezkel, Maiberger, Roy-Gan, Zajonts, Etai
Format Patent
LanguageEnglish
Published 21.05.2024
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:Examples are disclosed that relate to improving speed and accuracy of touch input classification. In one example, a touch detection device includes an array of antennas configured to measure touch input and output a touch matrix of pixels having touch values corresponding to the touch input measured at each antenna of the array of antennas. The touch detection device further includes a neural network having an input layer including a plurality of nodes. Each node is configured to receive a touch value corresponding to a different pixel of the touch matrix. The neural network is configured to output classified touch data corresponding to the measured touch input based at least on the touch matrix.
Bibliography:Application Number: US202318193188