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Doctoral students from the Statler College captured best poster awards at the International Joint Conference on Biometrics held October 1-4, in Denver, Colorado.
Naman Kohli and Daksha Yadav, doctoral students in computer science, received a best poster award for their paper titled, “Synthetic Iris Presentation Attack Using iDCGAN.” Commercial iris recognition systems find it difficult to discriminate between synthetically generated iris images and real iris images. Kohli and Yadav’s research proposes a solution to this challenging problem by developing a novel algorithm to generate realistic looking synthetic iris images using a new framework called iris deep convolutional generative adversarial network.
Shruti Nagpal and Maneet Singh, WVU visiting research scholars from the Indraprastha Institute of Information Technology at Delhi, also received a best poster award. Their paper, “Gender and Ethnicity Classification of Iris Images Using Deep Class Encoder,” focused on using a novel supervised deep class-encoder algorithm to predict gender and ethnicity by analyzing iris images. The use of gender and ethnicity as a soft biometric trait improves the iris recognition performance, reduces the computational time and results in faster processing.