Incept-N: A Convolutional Neural Network based Classification Approach for Predicting Nationality from Facial Features

TL;DR

This paper introduces Incept-N, a CNN-based method for predicting nationality from facial features, achieving high accuracy and low misclassification, advancing AI applications in security and identification.

Contribution

The paper presents a novel CNN architecture specifically designed for nationality prediction from facial images, demonstrating improved accuracy over existing methods.

Findings

Achieved 93.6% average accuracy in nationality prediction

Low misclassification rate in facial feature classification

Demonstrated effectiveness of CNN in security-related identification tasks

Abstract

The nationality of a human being is a well-known identifying characteristic used for every major authentication purpose in every country. Albeit advances in the application of Artificial Intelligence and Computer Vision in different aspects, its contribution to this specific security procedure is yet to be cultivated. With a goal to successfully applying computer vision techniques to predict the nationality of a person based on his facial features, we have proposed this novel method and have achieved an average of 93.6% accuracy with very low misclassification rate.