Iris recognition and attendance using deep learning techniques

Abstract: Iris recognition is a highly effective and reliable biometric authentication technique, leveraging the unique and stable patterns within the iris. In this research, we present an innovative iris recognition system that harnesses the power of deep learning models and employs image similarity metrics to achieve robust and efficient iris classification. The primary aim of this study is to develop an accurate and rapid iris recognition system suitable for access control and attendance management applications. Through rigorous experimentation, we demonstrate the effectiveness of our proposed approach, showcasing its superiority over traditional feature-based methods. Our results showcase the potential of deep learning, specifically Convolutional Neural Networks (CNNs), in enhancing the accuracy and efficiency of iris recognition, making it an ideal solution for various biometric authentication scenarios.

Keywords: Biometric Authentication, Convolutional Neural Networks (CNNs), Deep Learning-Based Classification.