CNN-based Gender Prediction in Uncontrolled Environments

Abstract

With the increasing amount of data produced and collected, the use of artificial intelligence technologies has become inevitable. By using deep learning techniques from these technologies, high performance can be achieved in tasks such as classification and face analysis in the fields of image processing and computer vision. In this study, Convolutional Neural Networks (CNN), one of the deep learning algorithms, was used. The model created with this algorithm was trained with facial images and gender prediction was made. As a result of the experiments, 93.71% success rate was achieved on the VGGFace2 data set and 85.52% success rate on the Adience data set. The aim of the study is to classify low-resolution images with high accuracy.

Keywords

• cnn
• vggface2
• adience
• image classification
• gender classification
• cnn
• vggface2
• adience
• görüntü sınıflama
• cinsiyet sınıflama