Title : Enhanced Dual Authentication Using Multimodal Biometric Framework and Deep Learning Technique

Type of Material: Thesis
Title: Enhanced Dual Authentication Using Multimodal Biometric Framework and Deep Learning Technique
Researcher: Sowmiya Manoj, M
Guide: Arulselvi, S
Department: Department of Electrical and Electronics Engineering
Publisher: Bharath University, Chennai
Place: Chennai
Year: 2022
Language: English
Subject: Engineering
Engineering and Technology
Engineering Electrical and Electronic
Electrical Engineering
Engineering and Technology
Dissertation/Thesis Note: PhD; Department of Electrical and Electronics Engineering, Bharath University, Chennai, Chennai; 2022; D18EC507
Fulltext: Shodhganga

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035__|a(IN-AhILN)th_455141
040__|aBHAU_600073|dIN-AhILN
041__|aeng
100__|aSowmiya Manoj, M|eResearcher
110__|aDepartment of Electrical and Electronics Engineering|bBharath University, Chennai|dChennai|ein|0U-0446
245__|aEnhanced Dual Authentication Using Multimodal Biometric Framework and Deep Learning Technique
260__|aChennai|bBharath University, Chennai|c2022
300__|dDVD
502__|cDepartment of Electrical and Electronics Engineering, Bharath University, Chennai, Chennai|d2022|oD18EC507|bPhD
518__|d2022|oDate of Award
520__|aNetwork security is considered as the major component of information security. It is very much important to have a secured transmission of information along with networks and computers. Normally, cryptography is one of the practices for protecting information from unknown people or it is a science of sending a message to another person or party in a way that only the recipient can read the message. Now a day s the usage of deep learning methods increasing in several fields which involves recognition of biometric because of its automatic data learning indication. In this research work Heuristic CNN model is used to abstract the structures of palmprint. Biometric authentication is of various types namely DNA Matching, iris recognition, face recognition, finer geometry recognition, hand geometry recognition, and voice recognition. It can be obtained from one or more physical or behavior traits like fingerprints, iris, face, speech, hand geometry, etc.
650__|aElectrical Engineering|2UGC
650__|aEngineering and Technology|2AIU
653__|aEngineering
653__|aEngineering and Technology
653__|aEngineering Electrical and Electronic
700__|aArulselvi, S|eGuide
856__|uhttp://shodhganga.inflibnet.ac.in/handle/10603/437815|yShodhganga
905__|afromsg

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