CSI-based Gesture Recognition and Object Detection
dc.contributor.author | Zhao, Ruyin | |
dc.contributor.department | Electrical and Computer Engineering | |
dc.contributor.majorProfessor | Daji Qiao | |
dc.date | 2021-06-11T15:20:02.000 | |
dc.date.accessioned | 2021-08-14T03:35:25Z | |
dc.date.available | 2021-08-14T03:35:25Z | |
dc.date.copyright | Fri Jan 01 00:00:00 UTC 2021 | |
dc.date.embargo | 2021-04-18 | |
dc.date.issued | 2021-01-01 | |
dc.description.abstract | <p>Nowadays, Wi-Fi is closely related to our life as we use Wi-Fi to communicate everyday. At the same time, people are constantly exploring other uses of Wi-Fi. With the release of Channel State Information (CSI) measurement tool, we can achieve more accurate indoor activity and object detection. In order to make a better used of the combination of Wi-Fi sensing tools and data analytic methods, we first have a deep look at CSI and methods of signal processing. Then, we use CSI and SVM, KNN, Decision Tree, LSTM and Random Forest to perform gesture recognition and object detection.</p> | |
dc.format.mimetype | ||
dc.identifier | archive/lib.dr.iastate.edu/creativecomponents/830/ | |
dc.identifier.articleid | 1828 | |
dc.identifier.contextkey | 22546497 | |
dc.identifier.s3bucket | isulib-bepress-aws-west | |
dc.identifier.submissionpath | creativecomponents/830 | |
dc.identifier.uri | https://dr.lib.iastate.edu/handle/20.500.12876/arY49GZv | |
dc.source.bitstream | archive/lib.dr.iastate.edu/creativecomponents/830/CSI_based_Gesture_Recognition_and_Object_Detection___04182021.pdf|||Sat Jan 15 02:09:48 UTC 2022 | |
dc.subject.disciplines | Data Science | |
dc.subject.disciplines | Digital Communications and Networking | |
dc.subject.keywords | Wireless Sensing | |
dc.subject.keywords | Channel State Information (CSI) | |
dc.subject.keywords | Machine Learning | |
dc.subject.keywords | Gesture Recognition | |
dc.subject.keywords | Object Detection. | |
dc.title | CSI-based Gesture Recognition and Object Detection | |
dc.type | article | |
dc.type.genre | creativecomponent | |
dspace.entity.type | Publication | |
relation.isOrgUnitOfPublication | a75a044c-d11e-44cd-af4f-dab1d83339ff | |
thesis.degree.discipline | Computer Engineering | |
thesis.degree.level | creativecomponent |
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