ARIF: Autonomous Recognition In the Field
Authors: Abubakr Osama Abubakr Osman
Journal: International Journal Of Automation And Digital Transformation
Volume: Vol 3 Issue 1
Keywords: biometrics, facial recognition, AI, ML, Computer Vision, Identification, Security, National Security, Homeland Security, Siamese Neural Networks, Convolutional Neural Networks
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.
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