01707nas a2200229   4500000000100000000000100001008004100002260001200043653001300055653001800068653003900086653002300125100001500148700001700163700001800180245006300198856009900261300001000360490000600370520108700376022001401463       2020                            d  c03/202010aBiometry10aDeep Learning10aConvolutional Neural Network (CNN)10aSclera Recognition1 aB S Harish1 aM S Maheshan1 aN Nagadarshan00aA Convolution Neural Network Engine for Sclera Recognition  uhttps://www.ijimai.org/journal/sites/default/files/files/2019/03/ijimai20206_1_9_pdf_52009.pdf  a78-830 v63 aThe world is shifting to the digital era in an enormous pace. This rise in the digital technology has created plenty of applications in the digital space, which demands a secured environment for transacting and authenticating the genuineness of end users. Biometric systems and its applications has seen great potentials in its usability in the tech industries. Among various biometric traits, sclera trait is attracting researchers from experimenting and exploring its characteristics for recognition systems. This paper, which is first of its kind, explores the power of Convolution Neural Network (CNN) for sclera recognition by developing a neural model that trains its neural engine for a recognition system. To do so, the proposed work uses the standard benchmark dataset called Sclera Segmentation and Recognition Benchmarking Competition (SSRBC 2015) dataset, which comprises of 734 images which are captured at different viewing angles from 30 different classes. The proposed methodology results showcases the potential of neural learning towards sclera recognition system.  a1989-1660