Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Abstract- The most dependable security function on cellphones is face recognition, which is used for security in public areas, railroads, and airports. When a face mask is worn, face detection becomes more challenging. Most nations have laws requiring people to wear face masks in order to prevent the spread of Covid-19 in public areas and on public transit. The more recent addition to smartphone security mechanisms, among passwords, pins, and fingerprints, is facial recognition and authentication. Finding the person wearing a mask on their face is the aim of this investigation. For security purposes, we can recognize robbers in rail and airport terminals. Businesses frequently employ facial recognition as an authentication technique. It aims to detect the person with a facial mask covering their face[1].
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Cite Article:
"Masked Facial Recognition In Security Systems Based On Deeplearning", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 4, page no.880 - 886, April-2024, Available :http://www.ijrti.org/papers/IJRTI2404122.pdf
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000205256
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator