ARTIFICIAL INTELLIGENCE-BASED PERSON IDENTIFICATION ALGORITHM

Abstract

This paper presents a comprehensive study of person identification algorithms based on artificial intelligence (AI), focusing on biometric data processing. Person identification plays a crucial role in security systems, banking, and personalized services. We explore algorithmic approaches that utilize facial recognition, iris scanning, and voice patterns. The study introduces a hybrid AI model combining Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) to increase recognition accuracy. Our model is trained and tested on benchmark datasets, and its performance is compared with conventional systems. Experimental results demonstrate that the proposed approach significantly improves identification precision and recall while reducing false-positive rates.