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Dataset for Air-writing recognition based on Ultra-wide band Radar Sensor

RMIT University, Australia
Akram Al-Hourani (Aggregated by) Haytham Fayek (Aggregated by) Nermine Hendy (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25439/rmt.20225907.v2&rft.title=Dataset for Air-writing recognition based on Ultra-wide band Radar Sensor&rft.identifier=10.25439/rmt.20225907.v2&rft.publisher=RMIT University, Australia&rft.description= Dataset for Air-writing recognition based on Ultrawideband Radar Sensor (Xethru X4-M03 from Novelda). The collected dataset includes air-written numbers from 0 to 9 using a uni-stroke writing technique. The Dataset contains 4 sub-folders and a MATLAB script. The dataset ia provided in CSV, MAT, and PNG formats.Please read the attached Dataset Description pdf file to understand the radar dataset collection setup, the included folders, the data format, and how to use the data for the air-writing recognition application.&rft.creator=Akram Al-Hourani&rft.creator=Haytham Fayek&rft.creator=Nermine Hendy&rft.date=2022&rft_rights= https://creativecommons.org/licenses/by-nc/4.0/&rft_subject=Digital electronic devices&rft_subject=Electronic device and system performance evaluation, testing and simulation&rft_subject=Electronic sensors&rft_subject=Electronics, sensors and digital hardware not elsewhere classified&rft_subject=Radio frequency engineering&rft_subject=Air-Writing&rft_subject=Radar signal processing&rft_subject=Deep Learning Applications&rft_subject=deep learning dataset&rft_subject=Xethru X4-M03&rft_subject=ultra-wide band radar&rft_subject=hand gesture recognition&rft_subject=Air-writing recognition&rft_subject=Range-Doppler&rft_subject=signal processing technology&rft_subject=radar signal processing&rft_subject=machine Learning&rft_subject=Neural Network&rft_subject=Fast Fourier transform (FFT)&rft.type=dataset&rft.language=English Access the data
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 Dataset for Air-writing recognition based on Ultrawideband Radar Sensor (Xethru X4-M03 from Novelda). The collected dataset includes air-written numbers from 0 to 9 using a uni-stroke writing technique. The Dataset contains 4 sub-folders and a MATLAB script. The dataset ia provided in CSV, MAT, and PNG formats.


Please read the attached Dataset Description pdf file to understand the radar dataset collection setup, the included folders, the data format, and how to use the data for the air-writing recognition application.

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Air-Writing | Air-writing recognition | Deep Learning Applications | Digital electronic devices | Electronic device and system performance evaluation, testing and simulation | Electronic sensors | Electronics, sensors and digital hardware not elsewhere classified | Fast Fourier transform (FFT) | Neural Network | Radar signal processing | Radio frequency engineering | Range-Doppler | Xethru X4-M03 | deep learning dataset | hand gesture recognition | machine Learning | radar signal processing | signal processing technology | ultra-wide band radar |

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