Age And Gender Detection Using Deep Learning - Netrali Shashikant Badve; Shreya Dattatray Dagade; Samiksha Satish Sundechamutha; Punam Prabhakar Deshmukh; V Panchal R (International Journal of Progressive Research in Science and Engineering, 2023)
Age and gender classification has become applicable to an extending measure of applications, particularly resulting to the ascent of social platforms and social media. Regardless, execution of existing strategies on real-world images is still fundamentally missing, especially when considered the immense bounced in execution starting late reported for the related task of face acknowledgment. In this project we exhibit that by learning representations through the use of significant Convolutional Neural Network (CNN) is used to extract the features from the input images and classifies the intermediate results. After all this, there is a development of a deep learning model which is totally based on the CNN. Along with CNN and OpenCV we combine the publicly available datasets (such as UTK faces, Facial image) into a large set and train for best method. The main objective of this project is to build a gender and age detector that can predict the gender and age of a person’s face in an image using deep learning on an audience dataset Based on our results, we develop applications for age and gender prediction.