TY  - JOUR
TI  - An evolutionary-based image classification approach through facial attributes
AB  - With the recent developments in technology, there has been a significant increase in the studies on analysis
of human faces. Through automatic analysis of faces, it is possible to know the gender, emotional state, and even the
identity of people from an image. Of them, identity or face recognition has became the most important task which
has been studied for a long time now as it is crucial to take measurements for public security, credit card verification,
criminal identification, and the like. In this study, we have proposed an evolutionary-based framework that relies on
genetic programming algorithm to evolve a binary- and multilabel image classifier program for gender classification,
facial expression recognition, and face recognition tasks. The performance of the evolved program has been compared
with that of convolutional neural network, one of the most popular deep learning algorithms. The comparative results
show that the proposed framework outperformed the competitor algorithm. Therefore, it has been introduced to the
research community as a new binary- and multilabel image classifier framework
AU  - Zalluhoglu, Cemil
AU  - YILMAZ, Selim
DO  - 10.3906/elk-2003-75
PY  - 2021
JO  - Turkish Journal of Electrical Engineering and Computer Sciences
VL  - 29
IS  - 2
SN  - 1300-0632
SP  - 860
EP  - 874
DB  - TRDizin
UR  - http://search/yayin/detay/514942
ER  -