International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 185 - Number 29 |
Year of Publication: 2023 |
Authors: Sonika Malik, Suyash Awasthy, Shivansh Sondhi, Rachit Singh |
10.5120/ijca2023923043 |
Sonika Malik, Suyash Awasthy, Shivansh Sondhi, Rachit Singh . Convolutional Neural Networks for Prediction of Age and Gender. International Journal of Computer Applications. 185, 29 ( Aug 2023), 40-45. DOI=10.5120/ijca2023923043
Automatic age and gender prediction from face images has recently attracted important attention due to its wide range of operations in multitudinous facial analyses. We show in this study that exercising the Caffe Model Architecture of Deep Learning Framework; we were suitable to greatly enhance age and gender recognition by learning representations using deep convolutional neural networks (CNN). The designed methodology preprocesses the input image before performing point birth using the convolutional neural network (CNN) strategy. This network excerpts dimensional characteristics from the source face image, followed by the point selection strategy. The proposed system is estimated using bracket rate, perfection, and recall using Adience dataset, and real-world images parade excellent performance by achieving good prediction results and calculation time.