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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 5, 2024.
Abstract: This research aims to devise a distinct mathematical key for individual identification and recognition. This key, represented through signals, is constructed using Lagrange polynomials derived from the skeletal points. Consequently, we present this key as a novel fingerprint categorized within physiological fingerprints. It’s crucial to highlight that the primary application of this fingerprint is for remote individual identification, specifically excluding any bodily masking. Subsequently, we implement an artificial intelligence model, specifically a Convolutional Neural Network (CNN), for the automated detection of individuals. The proposed CNN is trained on an extensive dataset comprising 10000 real-world cases and augmented data. Our skeletal fingerprint recognition system demonstrates superior performance compared to other physiological fingerprints, achieving a remark-able 98% accuracy in detecting individuals at a distance.
Achraf BERRAJAA, Ayyoub El OUTMANI, Issam BERRAJAA and Nourddin SAIDOU, “Revolutionary AI-Driven Skeletal Fingerprinting for Remote Individual Identification” International Journal of Advanced Computer Science and Applications(IJACSA), 15(5), 2024. http://dx.doi.org/10.14569/IJACSA.2024.01505126
@article{BERRAJAA2024,
title = {Revolutionary AI-Driven Skeletal Fingerprinting for Remote Individual Identification},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.01505126},
url = {http://dx.doi.org/10.14569/IJACSA.2024.01505126},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {5},
author = {Achraf BERRAJAA and Ayyoub El OUTMANI and Issam BERRAJAA and Nourddin SAIDOU}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.