TY  - JOUR
TI  - CNN-based Gender Prediction in Uncontrolled Environments
AB  - 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.
AU  - Güneş, Engin
AU  - Yıldız, Kazım
AU  - Bas, Anil
DO  - 10.29130/dubited.763427
PY  - 2021
JO  - Düzce Üniversitesi Bilim ve Teknoloji Dergisi
VL  - 9
IS  - 2
SN  - 2148-2446
SP  - 890
EP  - 898
DB  - TRDizin
UR  - http://search/yayin/detay/497257
ER  -