Fingers Touch Detection
| 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.description | This paper was completed as part of the Summer Team Impact Project 2022. | |
| 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. | |
| 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). | |
| dc.identifier.uri | https://hdl.handle.net/1920/12973 | |
| dc.language.iso | en_US | |
| dc.rights | Attribution-NonCommercial-ShareAlike 3.0 United States | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-sa/3.0/us/ | |
| dc.subject | Object Detection | |
| dc.subject | Computer Vision | |
| dc.subject | Deep Learning | |
| dc.subject | Machine learning | |
| dc.title | Fingers Touch Detection | |
| dc.type | Article |