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dc.contributor.authorUNIYAL, ADITI
dc.contributor.authorJAIN, SAMYAK
dc.date.accessioned2023-12-15T11:17:59Z
dc.date.available2023-12-15T11:17:59Z
dc.date.issued2022-05
dc.identifier.urihttp://10.10.11.6/handle/1/12458
dc.description.abstractHow to accurately and effectively identify people has always been an interesting topic, both in research and in industry. With the rapid development of artificial intelligence in recent years, facial recognition gains more and more attention. Compared with the traditional card recognition, fingerprint recognition and iris recognition, face recognition has many advantages, including but limit to non-contact, high concurrency, and user friendly. It has high potential to be used in government, public facilities, security, e-commerce, retailing, education and many other fields. In the past framework face acknowledgment was done physically which required some investment and effort. Due to manual up keep there are numbers for hardships and obstructions exist in the framework. In the current circumstance this work is done by face affirmation structure. Various public places for the most part have perception cameras for video get and these cameras have their gigantic impetus for security reason. It is extensively perceived that the face affirmation has been accepted a huge part in perception outline work. An unbelievable choice of libraries is one of the essential reasons Python is the most known programming language used for AI. A library is a module or a social affair of modules dispersed by different sources like PyPi which consolidate a pre-made piece out of code that licenses customers to show up at some value or perform different exercises. The result would be a mechanized instrument for facial affirmation and separate movement message transported off mail close by various data. We draw a careful acknowledgment that people talk with structures that reflect humanlike outlooks unexpectedly, so they will interface with them in robot.en_US
dc.language.isoen_USen_US
dc.publisherGALGOTIAS UNIVERSITYen_US
dc.subjectComputer Science, Engineering, FACE RECOGNITION , PYTHONen_US
dc.subjectFace recognition, biometric identification, OS Module, Numpy, Computer Visionen_US
dc.titleRECOGNIZING FACES WITH PYTHONen_US
dc.typeTechnical Reporten_US


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