@article{A. Deepa and T.Sasipraba_2020, title={ Competence Of Cranio Facial Growth In Aphorizing Age Through Visage}, volume={13}, url={http://sersc.org/journals/index.php/IJCA/article/view/24721}, abstractNote={<p>This paper expounds the association of shape of the face in the process of age estimation. The estimation of age from the face is a very challenging task. There are various internal and external factors involved in the process of estimation. The face is identified with the facial features such as eyes, nose, mouth and the expressions retrieved from the face. The objective is to synthesize aging effects that are visibly availed from the face. The shape of a face varies from person to person. But the average shape ratio remains same of every age group. The shape of the face is categorized into age groups and the role of shape in the age estimation process is discussed in this paper. The shape features are stored in the database and the input image is identified for the shape value and the estimation is done based on the classification algorithm Deep Neuro Shape Classifier Algorithm. This DNSC algorithm uses the deep neural method for classification.</p&gt;}, number={03}, journal={International Journal of Control and Automation}, author={A. Deepa and T.Sasipraba}, year={2020}, month={May}, pages={139 - 147} }