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dc.contributor.advisor Neris, Luciano de Oliveira
dc.contributor.author Matthews, Justin
dc.date.accessioned 2022-08-19T17:48:49Z
dc.date.available 2022-08-19T17:48:49Z
dc.date.issued 2022-08
dc.identifier.uri http://hdl.handle.net/1920/12973
dc.description This paper was completed as part of the Summer Team Impact Project 2022. en_US
dc.description.abstract Object detection is a form of machine learning that utilizes computer vision and deep learning techniques. It can be used to identify targeted objects in images and videos with precise accuracy. For detecting hand gestures, the method most commonly used is computer vision. When using computer vision, there are some factors to consider that could impact the results of the experiment. Due to this, a variety of different techniques were developed in order to mitigate the significance those factors have on the data. This paper will present one technique to use when creating a machine to detect hand gestures. en_US
dc.description.sponsorship The Summer Team Impact Project (STIP) 2022 was funded by grants from the Office of Undergraduate Education, The Office of Student Scholarship, Creative Activities, and Research (OSCAR), and the Office of Community Engagement and Civic Learning (CECIL). en_US
dc.language.iso en_US en_US
dc.rights Attribution-NonCommercial-ShareAlike 3.0 United States en_US
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/us/
dc.subject Object Detection en_US
dc.subject Computer Vision en_US
dc.subject Deep Learning en_US
dc.subject Machine Learning en_US
dc.title Fingers Touch Detection en_US
dc.type Article en_US


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