  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.
