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Q4 2024 Vol. 20 · No. 2 · pp. 391-408

ARIF: Autonomous Recognition in the Field Enhancing National Security with Computer Vision-Based Facial Recognition

Abubakr Osman
10.54878/z68s0z54 2,258 Views 0 Citations
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2,258
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Vol. 20, No.2
Volume / Issue
391-408
Pages
Abstract

Through a novel research approach that employs a mix of Convolutional Neural architectures & Siamese Neural Nets, we propose a viable mechanism that focuses on leveraging these groundbreaking advancements, through the utilization of deep learning algorithms we were able to effectively & accurately identify and authenticate individuals based on unique facial features derived from machine learnt embeddings. In The ARIF Project we implement the proposed architecture models through utilization of developer friendly modules like the python facial recognition library, the OpenCV framework & Jupiter Notebooks, performing the necessary product development, market research and product analysis throughout the development process, finally deliver a refined & minimalistic solution that not only fills market gaps but also serves as a solid foundation for rapid adoption & deployment.

Cite this Article (APA)
Abubakr, O. (2024). ARIF: Autonomous Recognition in the Field Enhancing National Security with Computer Vision-Based Facial Recognition. International Journal of Automation and Digital Transformation, 20(2), 391-408. https://doi.org/10.54878/z68s0z54
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Published in
Quartile Q4
AMS Score 58
Field Engineering & Technology
Publisher Emirates Scholar Center for Researc
Country 🇦🇪 UAE
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Authors
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Abubakr Osman
Publication Details
Year 2024
Volume 20
Issue 2
Pages 391-408
Language English
Added 23 Jun 2026