1. Advances in Iris and Ocular Recognition: An Insight into Trends 2. Unlocking the Full Potential of Iris Recognition with Deep Learning 3. Real-Time Online Framework for Accurate Detection, Segmentation, and Recognition of Irises 4. Enhancing Iris Recognition Accuracy through Dilated Residual Features 5. Iris Recognition with Deep Learning Across Spectrums 6. Semantics-Assisted Convolutional Neural Network for Accurate Periocular Recognition 7. Deep Neural Network with Focused Attention on Critical Periocular Regions 8. Dynamic Iris Recognition through Multi-Feature Collaboration 9. Position-Specific Convolutional Neural Network to Accurately Match Iris and Periocular Images 10. Securing the Metaverse with Egocentric Iris Recognition via AR/VR/MR Devices 11. Inference and Future Pathways: Reflections and Exploration of New Horizons

Provides insightful algorithmic details into highly efficient and precise iris recognition using deep neural networks Unveils a collection of previously unpublished results and in-depth explanations of advanced ocular recognition algorithms Presents iris recognition algorithms specifically designed to bolster metaverse security, featuring specialized techniques for iris detection, segmentation, and matching Offers illustrative examples and comparative analysis, establishing reliability and confidence in deep learning-based methods over widely used conventional methods Provides access to the original codes and databases