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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM13429

Face identification for Law Enforcement

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM13429

Volume:

6 |

5 |

May 2022

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM13429

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

KA

Kshitija Aher

VB

Vidhi Bhansali

PC

Preeti Chintaluri

MV

Meghna Verma

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Abstract

We all recognize that face detection is a sort of synthetic intelligence (AI) era that has grow to be an imperative a part of our normal lives, with results on nearly each element of our lives. In diverse fields, there may be a want for better accuracy and better pace for detection and popularity. However, the accuracy of the identity isn’t always precisely dependable in lots of cases. In this paper we gift a incredibly correct face popularity version the use of OpenCV and dlib libraries. One of the very best methods to become aware of someone‘s individuality is to examine their face. Face popularity is a machine for figuring out someone with the aid of using the use of private traits of the person. An individual’s face is diagnosed with the aid of using a system such as phases, specifically face detection, in which this system happens in no time in humans, besides in situations in which the item could be very near with the aid of using, and the introduction, which identifies a face as a unmarried individual. Here, we’ve additionally mentioned approximately detecting faces in a video frame. The most important difficulty in identity and popularity of faces is the storage, on this paper we’ve additionally addressed that problem with the aid of using handiest storing the facial capabilities in place of storing faces directly.

KEYWORDS

dlib face detection artificial intelligence machine learning deep learning CNN.

Cite This Article

Kshitija Aher, Vidhi Bhansali, Preeti Chintaluri, Meghna Verma, "Face identification for Law Enforcement," International Journal of Scientific Research in Engineering and Management, vol. 6, no. 5, May 2022. https://doi.org/10.55041/IJSREM13429

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Publication Date

5/21/2022

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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5

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Conflict of Interest

The authors declare no conflict of interest related to this research work.

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