• C Yasoda
• Shaik Taj Mahaboob
• P Naga Mallaiah

Latterly, We propose a convolutional neural network (CNN) based architecture for both age and gender recognition, here we use Gabor filter response as input. The architecture is trained to label the input images into eight ranges of age and two types of gender. This method shows improvement of accuracy in both age and gender classification compared to state-of-the-art methods. Here we are also observe that increasing the width of neural network can improve the accuracy of overall system. Age and gender recognition has owing its important role in user-friendly intelligent systems.

convolutional neural networks, gabor filter, classification, deep learning.

"A COMPREHENSIVE SURVEY OF AGE AND GENDER CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK AND GABOR FILTER", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.309-312, March-2019, Available :http://www.jetir.org/papers/JETIRAK06059.pdf

"A COMPREHENSIVE SURVEY OF AGE AND GENDER CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK AND GABOR FILTER", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp309-312, March-2019, Available at : http://www.jetir.org/papers/JETIRAK06059.pdf