Iris recognition has been an interesting subject for many research studies in the last two decades and has raised many challenges for the researchers. One new and interesting challenge in the iris studies is gender recognition using iris images. Gender classification can be applied to reduce processing time of the identification process. On the other hand, it can be used in applications such as access control systems, and gender-based marketing and so on. To the best of our knowledge, only a few numbers of studies are conducted on gender recognition through analysis of iris images.

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[1] Saeed Aryanmehr, Farsad Zamani Boroujeni, "Iris Super Resolution Dataset", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/3237-be47. Accessed: Jul. 19, 2024.
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doi = {10.21227/3237-be47},
url = {http://dx.doi.org/10.21227/3237-be47},
author = {Saeed Aryanmehr; Farsad Zamani Boroujeni },
publisher = {IEEE Dataport},
title = {Iris Super Resolution Dataset},
year = {2019} }
TY - DATA
T1 - Iris Super Resolution Dataset
AU - Saeed Aryanmehr; Farsad Zamani Boroujeni
PY - 2019
PB - IEEE Dataport
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Saeed Aryanmehr, Farsad Zamani Boroujeni. (2019). Iris Super Resolution Dataset. IEEE Dataport. http://dx.doi.org/10.21227/3237-be47
Saeed Aryanmehr, Farsad Zamani Boroujeni, 2019. Iris Super Resolution Dataset. Available at: http://dx.doi.org/10.21227/3237-be47.
Saeed Aryanmehr, Farsad Zamani Boroujeni. (2019). "Iris Super Resolution Dataset." Web.
1. Saeed Aryanmehr, Farsad Zamani Boroujeni. Iris Super Resolution Dataset [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/3237-be47
Saeed Aryanmehr, Farsad Zamani Boroujeni. "Iris Super Resolution Dataset." doi: 10.21227/3237-be47