  The Convolutional Neural Network has amazed us with its usage on several
applications. Age range estimation using CNN is emerging due to its application
in myriad of areas which makes it a state-of-the-art area for research and
improve the estimation accuracy. A deep CNN model is used for identification of
people's age range in our proposed work. At first, we extracted only face
images from image dataset using MTCNN to remove unnecessary features other than
face from the image. Secondly, we used random crop technique for data
augmentation to improve the model performance. We have used the concept of
transfer learning in our research. A pretrained face recognition model i.e
VGG-Face is used to build our model for identification of age range whose
performance is evaluated on Adience Benchmark for confirming the efficacy of
our work. The performance in test set outperformed existing state-of-the-art by
substantial margins.
