In the last decade, biometric techniques for person identification have gained more popularity. Different researchers have proposed various algorithms for feature extraction and classification. Deep learning is a new universally adopted method for classification and regression purpose. Compared to machine learning it is easiest way to train a deep neural network as it does not require feature extraction step. Only the requirement is it needs a voluminous database. In this paper we propose a “AlexNet” a pre-trained network for gender prediction from human iris. We implemented AlexNet for transfer learning based on feature extraction method. In this iris features are extracted using different intermediate layers. These features are further classified using multi-class SVM classifier. We achieved promising results for the proposed method.

Deep neural networks, Deep learning, AlexNet, Iris biometrics, Transfer learning

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