Iris recognition is a secure biometric technology known for its stability and privacy. With no two irises being identical and little change throughout a person's lifetime, iris recognition is considered more reliable and less susceptible to external factors than other biometric recognition methods. Unlike traditional machine learning-based iris recognition methods, deep learning technology does not rely on feature engineering and boasts excellent performance. This paper collects 120 relevant papers to summarize the development of iris recognition based on deep learning. We first introduce the background of iris recognition and the motivation and contribution of this survey. Then, we present the common datasets widely used in iris recognition. After that, we summarize the key tasks involved in the process of iris recognition based on deep learning technology, including identification, segmentation, presentation attack detection, and localization. Finally, we discuss the challenges and potential development of iris recognition. This review provides a comprehensive sight of the research of iris recognition based on deep learning.
翻译：Iris 识别是一种安全的生物鉴别技术,以其稳定性和隐私而闻名。由于在一个人的一生中,没有两条界限是相同的,没有什么变化,因此,Iris 识别被认为比其他生物鉴别方法更可靠,比其他生物鉴别识别方法更不易受到外部因素的影响。与传统的基于机器学习的虹膜识别方法不同,深层学习技术并不依赖于特征工程学,并称其业绩优异。本文件收集了120份相关文件,以总结基于深层学习的虹膜识别发展动态。我们首先介绍了虹膜识别背景以及这次调查的动机和贡献。然后,我们介绍了在虹膜识别中广泛使用的共同数据集。之后,我们总结了基于深层学习技术的虹膜识别过程所涉及的关键任务,包括识别、分解、演示攻击探测和本地化。最后,我们讨论了虹膜识别的挑战和潜在发展。本审查全面介绍了基于深层学习的对虹膜识别的研究。</s>
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