Author(s): Dr. Manju Arora, Sahil Sharma and Mohd. Asif Khan

Abstract: In this research work, we explore the field of computer vision with a focus on creating a powerful and versatile framework. Our work leverages deep learning around important tasks such as object detection, age estimation, and gender estimation. By integrating the Mask R-CNN model for object detection and the Deep Face library for age and gender estimation, we propose a solution that transcends the boundaries of one objective. Our approach includes careful information before improving the quality of input images, which demonstrates the efficiency of our model. The Mask R-CNN model provides guidance in object detection by demonstrating the ability to identify and find objects in images. This is the basis for the next project, where we will turn it into age and gender estimation using the Deep Face library. Our test results show not only successful identification of people with reliable scores, but also accurate age and gender predictions. We discuss the complexity of our approach, acknowledge its strengths, and directly address issues that arise when using it.

DOI: 10.33545/27076571.2024.v5.i1a.78

Pages: 22-29 | Views: 312 | Downloads: 170

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