| dc.contributor.author | Li, A | en_US |
| dc.contributor.author | Bodanese, E | en_US |
| dc.contributor.author | Luo, F | en_US |
| dc.contributor.author | Hou, T | en_US |
| dc.contributor.author | Wu, K | en_US |
| dc.date.accessioned | 2023-05-03T15:11:49Z | |
| dc.date.issued | 2022-01-01 | en_US |
| dc.identifier.isbn | 9781665494571 | en_US |
| dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/86128 | |
| dc.description.abstract | In this paper, we propose a cost-effective ultra-wideband (UWB) communication system for gesture recognition in a smart home environment, where the interference issues can be beneficially solved. In the proposed UWB communication system, the gesture trajectories obtained by positioning are employed for recognizing human gestures. To this end, we firstly collect the datasets of four different fine-grained gesture activities. Then, we integrate the squeeze-and-excitation block into the convolutional neural network seamlessly for gesture recognition, namely the SE-ConvlD model, which achieves an overall accuracy of 99.48%. | en_US |
| dc.format.extent | 825 - 830 | en_US |
| dc.title | The Ultra-Wideband Communication System: A Human Gesture Recognition Approach | en_US |
| dc.type | Conference Proceeding | |
| dc.rights.holder | © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |
| dc.identifier.doi | 10.1109/HPCC-DSS-SmartCity-DependSys53884.2021.00133 | en_US |
| pubs.notes | Not known | en_US |
| pubs.publication-status | Published | en_US |
| rioxxterms.funder | Default funder | en_US |
| rioxxterms.identifier.project | Default project | en_US |
