  Automatic age estimation from real-world and unconstrained face images is
rapidly gaining importance. In our proposed work, a deep CNN model that was
trained on a database for face recognition task is used to estimate the age
information on the Adience database. This paper has three significant
contributions in this field. (1) This work proves that a CNN model, which was
trained for face recognition task, can be utilized for age estimation to
improve performance; (2) Over fitting problem can be overcome by employing a
pretrained CNN on a large database for face recognition task; (3) Not only the
number of training images and the number subjects in a training database effect
the performance of the age estimation model, but also the pre-training task of
the employed CNN determines the performance of the model.
