Main Article Content

Abstract

It's a fairly simple task for humans to determine the gender of an individual using certain facial features, although it is difficult for machines to perform an equivalent task.  Within the past decade, unimaginable steps have been taken to automatically predict the gender from a face image.  The human face has certain distinctive features such as eyes, nose, lips, etc., which can be analyzed to classify humans into two basic genders: Male and Female.   This project aims at achieving a similar goal of detecting gender from face images.  The basic tool used in the project is Convolutional Neural Network (CNN) along with the use of the Programming language Python.  In recent years, face detection has achieved considerable attention from researchers in biometrics, pattern recognition, and computer vision groups.  There are countless security and forensic applications requiring the use of face recognition technologies which have motivated us to explore this area and start with this project.

Keywords

CNN Gender Machine Learning Python Deep Learning

Article Details

Author Biographies

Devjyoti Saha, Bengal Institute of Technology

Department of Computer Science and Engineering

Diptangshu De, Bengal Institute of Technology

Department of Computer Science and Engineering

Pratick Ghosh, Bengal Institute of Technology

Department of Computer Science and Engineering

Sourish Sengupta, Bengal Institute of Technology

Department of Computer Science and Engineering

Tripti Majumdar, Bengal Institute of Technology

Department of Computer Science and Engineering

Citations
Saha, D., De, D., Ghosh, P., Sengupta, S., & Majumdar, T. (2020). Classification of Gender from Human Facial Images using Convolutional Neural Networks. [email protected] - Preprint Archive, 1(1). https://doi.org/10.36375/prepare_u.a61

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