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Few-Shot Learning for Biometric Verification. (arXiv:2211.06761v1 [cs.CV])
Nov. 15, 2022, 2:15 a.m. | Umaid M. Zaffar, Marium Aslam, Muhammad Imran Malik, Saad Bin Ahmed
cs.CV updates on arXiv.org arxiv.org
In machine learning applications, it is common practice to feed as much
information as possible. In most cases, the model can handle large data sets
that allow to predict more accurately. In the presence of data scarcity, a
Few-Shot learning (FSL) approach aims to build more accurate algorithms with
limited training data. We propose a novel end-to-end lightweight architecture
that verifies biometric data by producing competitive results as compared to
state-of-the-art accuracies through Few-Shot learning methods. The dense layers
add …
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