From Synthetic Data to Real Palm Vein Identification: a Fine-Tuning Approach

Author:

Hernández-García Ruber1,Salazar-Jurado Edwin H.2,Barrientos Ricardo J.3,Castro Francisco Manuel4,Ramos-Cózar Julián4,Guil Nicolás4

Affiliation:

1. CIEAM Research Center, LITRP Laboratory Universidad Católica del Maule,Talca,Chile

2. DMMA PhD Program, LITRP Laboratory Facultad de Ciencias Báicas Universidad Católica del Maule,Talca,Chile

3. LITRP Laboratory, Universidad Católica del Maule,Faculty of Engineering Sciences,Dept. DCI,Talca,Chile

4. Universidad of Mólaga,Dept. of Computer Architecture,Málaga,Spain

Funder

Agencia Nacional de Investigación y Desarrollo (ANID)

ANID FONDECYT Iniciación en Investigación 2022

Chinese Academy of Sciences' Institute of Automation (CASIA)

Publisher

IEEE

Reference27 articles.

1. On the Performance of Pretrained CNN Aimed at Palm Vein Recognition Application

2. A survey on synthetic biomet-rics;makrushin;IEEE Access,2023

3. Palm vein recognition based on end-to-end convolutional neural network;lu;Journal of South Medical University,2019

4. Applications of Different CNN Architectures for Palm Vein Identification

5. FYO: A Novel Multimodal Vein Database With Palmar, Dorsal and Wrist Biometrics

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