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ISSN No: 2349-2287 (P) | E-ISSN: 2349-2279 (O) | E-mail: editor@ijiiet.com

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International Research Journal of Infinite Innovations in Engineering and Technology (IJIIET)

| ISSN Approved Journal | Impact factor: 7.521 | Follows UGC CARE Journal Norms and Guidelines |

| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | Impact factor 7.521 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing) in all Major Database & Metadata, Citation Generator

Title : Age and Gender Estimation

Author : THIPPALURU ISWARYA,, JANGILI RAVI KISHORE, K BALAJI SUNIL CHANDRA

Abstract :

With the proliferation of social media and platforms, automatic age and gender categorization has gained relevance in a growing number of applications. When compared to the recent reported great jumps in performance for the related job of face recognition, the performance of present approaches on real-world photographs is still severely insufficient. We demonstrate in this research that deep-convolution neural network (CNN) models (age_net.caffemodel, gender_net.caffe model) can learn representations and significantly improve performance on these tasks. So, even with a little quantity of training data, we suggest a basic convolution net design.

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