INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (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)
Facial recognition, a technique that utilizes
various features of the face to verify and
identify individuals, is becoming more
popular in various industrial applications
including security, surveillance, and access
control. Due to machine learning's capability
to learn complicated patterns from enormous
datasets, it's an effective approach for facial
recognition. The utilization of machine
learning for face recognition is a
methodology comprising three distinct
stages: face detection, feature extraction,
and classification. The first phase involves
an algorithm that recognizes the facial
features in a given image or video source.
Following this, the feature extraction
process identifies key geometric and textural
characteristics from the detected face.
Lastly, the extracted data is run through a
classification algorithm to determine its
corresponding class - usually ascertaining
identity information. To address the
challenge of recognizing faces accurately
convolutional neural networks (CNNs),
support vector machines, and random forests
are some examples of machine learning
algorithms that have been identified. CNNs
are especially promising as they can identify
hierarchical representations within images
thereby providing better accuracy. With that
said even though these modeling techniques
show promise they still struggle with
problems posed by uncontrolled lighting
conditions, pose variations and occlusions.
Moreover like any facial recognition
technology needs to meet strict ethical
standards because it also brings up privacy
concerns. From healthcare to security and
entertainment industries, facial recognition
powered by machine learning is
revolutionizing how we see automation. As
datasets grow larger and more sophisticated
algorithms emerge, we can expect
"Face Recognition Using Machine Learning"", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 4, page no.c293-c296, April-2023, Available :http://www.ijnrd.org/papers/IJNRD2304237.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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