Artificial Intelligence-Enabled Blockchain Technology and Digital Twin for Smart Hospitals

14Framework for Gender Detection Using Facial Countenances

Shyla^1*, Shalu² and Mohit Dayal¹

¹Bharati Vidyapeeth’s College of Engineering, Delhi, India

²Manav Rachna University, Faridabad, Haryana, India

Abstract

This research paper delves into the domain of gender detection from facial images, presenting an innovative approach leveraging state-of-the-art machine learning techniques. With the aim of achieving heightened accuracy and robustness, the study builds upon convolutional neural networks (CNNs), a potent tool in computer vision. The investigation critically examines the limitations of existing methodologies, particularly those reliant on support vector machines (SVM) and datasets like FERET. Notably, these approaches are constrained by controlled environments, emphasizing the need for advancements that transcend such limitations.

The research unfolds with a threefold objective: to scrutinize technological advancements in artificial intelligence, particularly within computer vision, for precise gender prediction; to comprehend the intricate psychological and sociological factors influencing gender perception; and to scrutinize the ethical implications accompanying the deployment of gender recognition technology. The code implementation showcases a meticulous training process involving data preparation, image augmentation, and the formulation of a CNN model. The evaluation phase encompasses traditional metrics such as accuracy and loss, complemented by real-time gender ...