Gender classification from fused multi-fingerprint types
Author:
Affiliation:
1. Department of Electronic Engineering, University of Nigeria, Nsukka, Enugu State, Nigeria
Publisher
Informa UK Limited
Subject
Information Systems and Management,Computer Science Applications,Software
Link
https://www.tandfonline.com/doi/pdf/10.1080/19393555.2020.1741742
Reference36 articles.
1. Impact of digital fingerprint image quality on the fingerprint recognition accuracy
2. Effective training of convolutional neural networks for face-based gender and age prediction
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