Iris Segmentation Using Feature Channel Optimization for Noisy Environments-Reference-Cited by-同舟云学术

Iris Segmentation Using Feature Channel Optimization for Noisy Environments

Published:2020-09-04 Issue:6 Volume:12 Page:1205-1216
ISSN:1866-9956
Container-title:Cognitive Computation
language:en
Short-container-title:Cogn Comput

Author:

Hao Kangli,Feng Guorui,Ren Yanli,Zhang Xinpeng

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Cognitive Neuroscience,Computer Science Applications,Computer Vision and Pattern Recognition

Link

https://link.springer.com/content/pdf/10.1007/s12559-020-09759-9.pdf

Reference25 articles.

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2. Albadarneh A, Albadarneh I, Alqatawna J. Iris recognition system for secure authentication based on texture and shape features. IEEE jordan conference on applied electrical engineering and computing technologies (AEECT). IEEE, 2015; 2015. p. 1–6.

3. Gao C, Feng G, Ren Y, Liu L. Iris segmentation based on improved u-net network model. IEICE Transactions on Fundamentals of Electronics. Commun Comput Sci 2019;102(8):982–985.

4. Ronneberger O, Fischer P, Brox T. U-net: convolutional networks for biomedical image segmentation. International conference on medical image computing and computer-assisted intervention. New York: Springer; 2015. p. 234–241.

5. Yu F, Koltun V. 2015. Multi-scale context aggregation by dilated convolutions arXiv:151107122.

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