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Deep Learning for Iris Recognition: A Survey
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AI
DOI：10.1145/3651306.png)
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摘要
En 中文
In this survey, we provide a comprehensive review of more than 200 articles, technical reports, and GitHub repositories published over the last 10 years on the recent developments of deep learning techniques for iris recognition, covering broad topics on algorithm designs, open-source tools, open challenges, and emerging research. First, we conduct a comprehensive analysis of deep learning techniques developed for two main sub-tasks in iris biometrics: segmentation and recognition. Second, we focus on deep learning techniques for the robustness of iris recognition systems against presentation attacks and via human-machine pairing. Third, we delve deep into deep learning techniques for forensic application, especially in post-mortem iris recognition. Fourth, we review open-source resources and tools in deep learning techniques for iris recognition. Finally, we highlight the technical challenges, emerging research trends, and outlook for the future of deep learning in iris recognition.
Keyword:
Iris recognition
deep learning
neural networks
期刊
IF:
28
论文数:
2.5K
被引数:
3.5W
机构
引用论文
T-Center: A Novel Feature Extraction Approach Towards Large-Scale Iris RecognitionT-center: 一种面向大规模虹膜识别的特征提取方法.png)
IEEE ACCESS
OAAI
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GeologyIF0
PREAI
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