Recognizing British Sign Language using Deep Learning: A Contact-less and Privacy-Preserving Approach

Hameed, H., Usman, M., Tahir, A., Imran, M. and Abbasi, Q. (2022) Recognizing British Sign Language using Deep Learning: A Contact-less and Privacy-Preserving Approach. [Data Collection]

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The dataset is about BSL in a privacy-preserving manner. In particular, radio frequency (RF) sensing was used to capture doppler frequency shifts due to Head and Hand movements. Xethru UWB Radar X4M03 was used for reception and transmission respectively. We consider fifteen classes for BSL movements. fifteen Signs such as drink, eat, help, stop, walk, confused, depressed, pleased, hate, sad, family, brother, father, mother, and sister were performed. Four subjects 1 male and 3 females participated in the experiments.

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College / School: College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
Date Deposited: 05 Dec 2022 09:36
URI: https://researchdata.gla.ac.uk/id/eprint/1350

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Hameed, H., Usman, M., Tahir, A., Imran, M. and Abbasi, Q. (2022); Recognizing British Sign Language using Deep Learning: A Contact-less and Privacy-Preserving Approach

University of Glasgow

DOI: 10.5525/gla.researchdata.1350

Retrieved: 2024-04-20

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