Iris Recognition Using A Deep Learning Approach
Iris recognition has been an lively research area during last few periods, because of its wide bids in security, from aerodromes to home security border control. Diverse structures and procedures have been projected for iris recognition in the ancient period. In this paper, we suggest an endwise deep learning framework for iris recognition based on convolutional neural network (CNN), which can mutually acquire the feature illustration and achieve acknowledgment. We train our model on a well-known iris recognition dataset using only a few training images from each class, and show hopeful results and enhancements over previous approaches. We also present a visualization technique which is able to perceive the important areas in iris images which can mostly influence the recognition results. We trust this framework can be commonly used for other biometrics recognition errands, helping to have a more ascendable and exact systems.