mlsanityData to 7 Oct 2026

Deep Learning for Iris Recognition: A Review

arXiv 2303.08514 ↗First posted 15 Mar 2023cs.CVcited by 4

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 58 of its 201 references that are in the map. First posted on arXiv 15 Mar 2023.

Builds on

58 of 201 references.

References · 58

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  4. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  5. 2017Mask R-CNNcited by 7,259
  6. 2016Densely Connected Convolutional Networkscited by 6,691
  7. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,845
  8. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,827
  9. 2022A ConvNet for the 2020scited by 3,545
  10. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,210
  11. 2016Xception: Deep Learning with Depthwise Separable Convolutionscited by 2,320
  12. 2019Searching for MobileNetV3cited by 1,984
38 more
  1. 2016Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Networkcited by 1,898
  2. 2020Knowledge Distillation: A Surveycited by 1,578
  3. 2015SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentationcited by 1,483
  4. 2016YOLO9000: Better, Faster, Strongercited by 1,429
  5. 2014Image Super-Resolution Using Deep Convolutional Networkscited by 1,218
  6. 2021Swin Transformer V2: Scaling Up Capacity and Resolutioncited by 1,215
  7. 2021EfficientNetV2: Smaller Models and Faster Trainingcited by 1,127
  8. 2016SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model sizecited by 1,054
  9. 2018Dual Attention Network for Scene Segmentationcited by 1,001
  10. 2015Accurate Image Super-Resolution Using Very Deep Convolutional Networkscited by 902
  11. 2021MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformercited by 636
  12. 2019Importance Estimation for Neural Network Pruningcited by 531
  13. 2021LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inferencecited by 475
  14. 2016RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentationcited by 463
  15. 2015Learning Deconvolution Network for Semantic Segmentationcited by 365
  16. 2020SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentationcited by 70
  17. 2019Post-mortem Iris Recognition with Deep-Learning-based Image Segmentationcited by 32
  18. 2020D-NetPAD: An Explainable and Interpretable Iris Presentation Attack Detectorcited by 26
  19. 2022Deep Learning for Iris Recognition: A Surveycited by 25
  20. 2017Synthetic Iris Presentation Attack using iDCGANcited by 17
  21. 2018Iris Recognition After Deathcited by 13
  22. 2020Demographic Bias in Presentation Attack Detection of Iris Recognition Systemscited by 13
  23. 2017An Experimental Study of Deep Convolutional Features For Iris Recognitioncited by 10
  24. 2018Presentation Attack Detection for Cadaver Iriscited by 10
  25. 2021Deep GAN-Based Cross-Spectral Cross-Resolution Iris Recognitioncited by 10
  26. 2017Gender-From-Iris or Gender-From-Mascara?cited by 9
  27. 2020Deep Learning-Based Feature Extraction in Iris Recognition: Use Existing Models, Fine-tune or Train From Scratch?cited by 9
  28. 2019Post-Mortem Iris Recognition Resistant to Biological Eye Decay Processescited by 8
  29. 2020Open Source Iris Recognition Hardware and Software with Presentation Attack Detectioncited by 7
  30. 2019Learning-Free Iris Segmentation Revisited: A First Step Toward Fast Volumetric Operation Over Video Samplescited by 5
  31. 2018A Benchmark for Iris Location and a Deep Learning Detector Evaluationcited by 4
  32. 2018Implications of Ocular Pathologies for Iris Recognition Reliabilitycited by 4
  33. 2018Robust Iris Segmentation Based on Fully Convolutional Networks and Generative Adversarial Networkscited by 4
  34. 2019Iris Recognition with Image Segmentation Employing Retrained Off-the-Shelf Deep Neural Networkscited by 4
  35. 2019Deep Neural Network and Data Augmentation Methodology for off-axis iris segmentation in wearable headsetscited by 4
  36. 2019Constrained Design of Deep Iris Networkscited by 4
  37. 2022Iris super-resolution using CNNs: is photo-realism important to iris recognition?cited by 4
  38. 2018SegDenseNet: Iris Segmentation for Pre and Post Cataract Surgerycited by 3

50 most cited of 58 All 58 (JSON)

Built on by

Cited by year

Citing papers per year: 2024: 3; 2025: 1.

4 papers.

  1. 2024Arabic Handwritten Text for Person Biometric Identification: A Deep Learning Approachcited by 1
  2. 2024VRBiom: A New Periocular Dataset for Biometric Applications of HMDcited by 1
  3. 2025Iris Style Transfer: Enhancing Iris Recognition with Style Features and Privacy Preservation through Neural Style Transfercited by 1
  4. 2024MsMemoryGAN: A Multi-scale Memory GAN for Palm-vein Adversarial Purificationcited by 0