Face Recognition LogIn System

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dc.contributor.advisorMd. Abu Obaidah
dc.contributor.authorMd. Ibrahim Khalil Ullah
dc.contributor.authorMd. Mehraj Uddin
dc.contributor.authorOali Ullah
dc.contributor.id1812015042
dc.contributor.id1813213643
dc.contributor.id1612545042
dc.coverage.departmentElectrical and Computer Engineering
dc.date.accessioned2025-04-17
dc.date.accessioned2025-04-17T09:29:58Z
dc.date.available2025-04-17T09:29:58Z
dc.date.issued2022
dc.description.abstractWe can identify human faces using a web camera which is known as Face Detection. This is a very effective technique in computer technology. There are used different types of attendance systems such as log in with the password, punch card, fingerprint, etc. With rapid growth in the application of AI, Access Control Systems are walking in a new technology lane. Powered by deep learning technologies or cognitive analytics, login pages can implement more secure, efficient, and easy to use authentication systems. In this project, we have introduced a Facial Recognition type LogIn System that can identify a specific face by analyzing and comparing patterns of a digital image. This system is the Tensorflow LogIn System based on face detection. Primarily, the device captures the face images and stores the captured images into the specific path of the computer relating the information into a database. When anybody tries to enter into any website through this LogIn System, the system captures the image of that particular person and matches the image with the stored image. If this image matches with the stored image then the system allows the person to enter the website, otherwise the system denies entry.
dc.description.degreeUndergraduate
dc.identifier.cd600000494
dc.identifier.print-thesisTo be assigned
dc.identifier.urihttps://repository.northsouth.edu/handle/123456789/1128
dc.language.isoen
dc.publisherNorth South University
dc.rights© NSU Library
dc.titleFace Recognition LogIn System
dc.typeThesis
oaire.citation.endPage43
oaire.citation.startPage1
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