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DC Field | Value | Language |
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dc.contributor.author | Sarsavadia, Riddhi | - |
dc.date.accessioned | 2019-08-29T10:14:56Z | - |
dc.date.available | 2019-08-29T10:14:56Z | - |
dc.date.issued | 2018-06-01 | - |
dc.identifier.uri | http://10.1.7.192:80/jspui/handle/123456789/8796 | - |
dc.description.abstract | Features of Human face can be used to identify human uniquely. This make Face recognition system(FRS) popular for many applications like security verification at gate in many organizations, for access control of confidential resources, identifying intruders by national defence, and many more. With time, researchers and practitioners are putting efforts to rectify and optimize Intelligent Face Recognition System for different perspective, e.g. optimizing for accuracy, time, and space complexity, accuracy for facial expression change with time, face captured at some degree of orientation, lightning condition,occlusions etc.. As a result, many algorithms are available for face recognition system. This dissertation work focus to optimize IFRS for four criteria: i) face captured at more than 45 orientation, ii) person wearing eyeglass of different shape and size. iii) Face recognition using IP camera. Hence, we name it as "Intelligent face recognition system". | en_US |
dc.publisher | Institute of Technology | en_US |
dc.relation.ispartofseries | 16MCEN17; | - |
dc.subject | Computer 2016 | en_US |
dc.subject | Project Report 2016 | en_US |
dc.subject | Computer Project Report | en_US |
dc.subject | Project Report | en_US |
dc.subject | 16MCEN | en_US |
dc.subject | 16MCEN17 | en_US |
dc.subject | NT | en_US |
dc.subject | NT 2016 | en_US |
dc.subject | CE (NT) | en_US |
dc.title | Intelligent Face Recognition System | en_US |
dc.type | Dissertation | en_US |
Appears in Collections: | Dissertation, CE (NT) |
Files in This Item:
File | Description | Size | Format | |
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16MCEN17.pdf | 16MCEN17 | 1.35 MB | Adobe PDF | ![]() View/Open |
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