Enhancing human iris recognition performance in unconstrained environment using ensemble of convolutional and residual deep neural network models

Research article (Soft Computing, 2019) · cited 29× · AI/ML
Press Enter · cited answer in seconds

Enhancing human iris recognition performance in unconstrained environment using ensemble of convolutional and residual deep neural network models

Summary

Enhancing human iris recognition performance in unconstrained environment using ensemble of convolutional and residual deep neural network models is a scholarly article[1].

Key Facts

  • Enhancing human iris recognition performance in unconstrained environment using ensemble of convolutional and residual deep neural network models's instance of is recorded as scholarly article[2].

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Enhancing human iris recognition performance in unconstrained environment using ensemble of convolutional and residual deep neural network models. Retrieved May 24, 2026, from https://4ort.xyz/entity/enhancing-human-iris-recognition-performance-in-unconstrained-environment-using-ensemble-of-convolutional-and-residual-d
MLA “Enhancing human iris recognition performance in unconstrained environment using ensemble of convolutional and residual deep neural network models.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/enhancing-human-iris-recognition-performance-in-unconstrained-environment-using-ensemble-of-convolutional-and-residual-d.
BibTeX @misc{4ortxyz_enhancing-human-iris-recognition-performance-in-unconstrained-environment-using-ensemble-of-convolutional-and-residual-d_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Enhancing human iris recognition performance in unconstrained environment using ensemble of convolutional and residual deep neural network models}}, year = {2026}, url = {https://4ort.xyz/entity/enhancing-human-iris-recognition-performance-in-unconstrained-environment-using-ensemble-of-convolutional-and-residual-d}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Enhancing human iris recognition performance in unconstrained environment using ensemble of convolutional and residual deep neural network models — https://4ort.xyz/entity/enhancing-human-iris-recognition-performance-in-unconstrained-environment-using-ensemble-of-convolutional-and-residual-d (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/enhancing-human-iris-recognition-performance-in-unconstrained-environment-using-ensemble-of-convolutional-and-residual-d · Last refreshed: