Deep Learning-Based Age Estimation and Gender Deep Learning-Based Age Estimation and Gender Classification for Targeted Advertisement
Muhammad Imran Zaman, Nisar Ahmed
2025-07-25
Summary
This paper talks about using deep learning, specifically a custom convolutional neural network, to estimate a person's age and gender from their face in order to help deliver better-targeted advertisements.
What's the problem?
Accurately guessing age and gender from images is hard because faces can vary a lot and many models either focus on one task or don't do both tasks well together, which limits how effective targeted ads can be.
What's the solution?
The researchers designed a special neural network that learns to recognize both age and gender at the same time by sharing the knowledge it gains from each task, which improves its ability to classify gender accurately and estimate age competitively.
Why it matters?
This matters because better age and gender detection helps advertisers show the right products to the right people, making advertising more effective and personalized.
Abstract
A custom CNN architecture for simultaneous age and gender classification from facial images improves performance by learning shared representations, achieving high gender classification accuracy and competitive age estimation.