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DC Field | Value | Language |
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dc.contributor.author | Sawhney, Vaibhav | - |
dc.contributor.author | Saini, Hemraj [Guided by] | - |
dc.date.accessioned | 2022-09-29T04:58:41Z | - |
dc.date.available | 2022-09-29T04:58:41Z | - |
dc.date.issued | 2019 | - |
dc.identifier.uri | http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/6964 | - |
dc.description.abstract | Signal Acknowledgment is the most supported and practicable answer for recover human connection with PCs and has been generally acknowledged as of late gratitude to its training in gaming gadgets, for example, Xbox, PS4,etc just as different gadgets, for example, workstations, Cell phone, and so forth of motions and especially the acknowledgment of hand motions is used in different applications, for example, openness support, emergency the board, drug and so on. This report delineates our fourth-year venture "Affirmation of motions", portraying the various bearings and techniques that are used for hand signal acknowledgment. Furthermore, it depicts numerous strategies used for advancement and its exact portrayal, demonstrates the yield accumulated and the tests executed to test the refined programming ancient rarity. Since hand motion acknowledgment is connected to two fundamental AI and picture handling fields, the report further depicts distinctive APIs and instruments that can be used to execute various methodologies and techniques in such territories. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Jaypee University of Information Technology, Solan, H.P. | en_US |
dc.subject | Gesture recognition | en_US |
dc.subject | Algorithm | en_US |
dc.title | Gesture Recognition | en_US |
dc.type | Project Report | en_US |
Appears in Collections: | B.Tech. Project Reports |
Files in This Item:
File | Description | Size | Format | |
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Gesture Recognition.pdf | 1.41 MB | Adobe PDF | View/Open |
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