Automatic Age and Gender Estimation using Deep Learning and Extreme Learning Machine (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Age and gender classification has become applicable to an extending measure of applications, particularly resultingto the ascent of social platforms and social media. Regardless, execution of existing strategies on real-world images is stillfundamentally missing, especially when considered the immense bounced in execution starting late reported for the related taskof face acknowledgment. In this paper we exhibit that by learning representations through the use of significant Convolutiona lNeural Network (CNN) and Extreme Learning Machine (ELM). CNN is used to extract the features from the input imageswhile ELM classifies the intermediate results. We experiment our architecture on the recent Adience benchmark for age andgender estimation and demonstrate it to radically outflank current state-of-the-art methods. Experimental results show that ourarchitecture outperforms other studies by exhibiting significant performance improvement in terms of accuracy and efficiency.