Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/564552
Title: | Face recognition in dynamic environment using deep neural network |
Researcher: | Dinesh, P S |
Guide(s): | Manikandan, M |
Keywords: | Computer Science Computer Science Information Systems computer vision data science Engineering and Technology face recognition technology |
University: | Anna University |
Completed Date: | 2024 |
Abstract: | After decades of research, it is exciting to see that face recognition newlinetechnology has entered the most flourishing era. Driven by the latest newlinedevelopment in data science and especially technical evolutions in computer newlinevision and pattern recognition, face recognition has achieved significant newlineprogress over the last three years. Shortly, people can expect many useful and newlineinteresting face recognition applications to be deployed in many situations. newlineThey can be used for identifying suspects, organizing your photos with family newlineand friends, and making computers better understand human beings. newlineBiometrics is a system used to recognize humans based on their newlinephysical or behavioural characteristics. Face recognition has been a dynamic newlineresearch area in the domains of pattern recognition and computer vision. Each newlineface in this world is unique and therefore it is an identity of humans. Due to newlineits uniqueness, this identity can be used for authentication and access control newlinein different applications. The primary aim of this research is to focus on face newlinerecognition and facial feature. It also includes other recently developed face newlinerecognition techniques and methods that are claimed to provide an effective newlineand accurate face recognition method. In addition, a novel method for newlinerecognizing a face is implemented. newlineImage recognition and representation have been the prime area of newlineresearch for which deep learning aids prominently in extracting salient newlinefeatures from an image, reducing dimensionality and preserving important newlineinformation. newline |
Pagination: | xvi,132p. |
URI: | http://hdl.handle.net/10603/564552 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 29.76 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 2.26 MB | Adobe PDF | View/Open | |
03_content.pdf | 94.82 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 10.82 kB | Adobe PDF | View/Open | |
05_chapter1.pdf | 161.38 kB | Adobe PDF | View/Open | |
06_chapter2.pdf | 139.29 kB | Adobe PDF | View/Open | |
07_chapter3.pdf | 956.1 kB | Adobe PDF | View/Open | |
08_chapter4.pdf | 1.44 MB | Adobe PDF | View/Open | |
09_annexures.pdf | 132.66 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 315.71 kB | Adobe PDF | View/Open |
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