Facial image Classification based on Gender

  • Navin kumar Agrawal, Amit kumar, Ayush khatri, Gagan gaur


The human face contains a very major and valuable amount of features and details regarding the person, like facial gestures, the gender of the person, and the age of the person. Human beings can easily identify and examine these kind of information easily, for example human traits like gender can be easily identifiable by the people, they are able to tell if the person is male or female just by looking at the face of the person. Similarly, they are able to estimate the age of the person and can easily tell whether the person is younger or older. On the either side, developing such applications that can recognize the persons by their face and can extract the information like age and gender is very critical and very challenging task for the computer vision, on which the upcoming future is going to get dependent which will be used in various important areas of our life, because of the demand of creating a generalized model that will work for all human beings. Prediction of the gender and estimation of the age of people from their facial images is still an on-going and active research problem. Several methods have been derived by the researchers in order to solve this particular problem but still, there is a lot of insufficiency between the requirements and reliable performance. In this research, an attempt is made to classify the human gender and estimate the age and further, the performance of the system will be improved on the finer level by using neural networks which will train itself to generate the output more precisely.

How to Cite
Ayush khatri, Gagan gaur, N. kumar A. A. kumar,. (2020). Facial image Classification based on Gender. International Journal of Advanced Science and Technology, 29(3), 3890 - 3896. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/5143