Deep Learning-Based Palmprint Recognition : Transfer Learning and Fine-Tuning Approaches

Language: English

Published by Globeedit, 2026

6630119401 / 9786630119404

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Softcover

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nach der Bestellung gedruckt Neuware - Printed after ordering - This work presents a deep learning-based palmprint recognition system to address the growing need for reliable biometric authentication. Traditional security methods relying on passwords or tokens often fail to distinguish authorized users from fraudsters, motivating the shift toward biometrics.Three pre-trained CNN architectures are used: VGG16, MobileNetV2, and DenseNet-121, combined with two techniques: transfer learning and fine-tuning. Two data strategies are explored: single-instance using one hand, and multi-instance using both hands, evaluated on the PolyU palmprint database with 100 subjects.Fine-tuning consistently outperforms transfer learning. DenseNet-121 achieved the best accuracy of 98.75%, followed by MobileNetV2 at 98.50% and VGG16 at 92.50%. Transfer learning yielded lower but competitive results. The multi-instance strategy produced stronger performance by providing richer biometric information from both hands.…

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Bibliographic details

Title
Deep Learning-Based Palmprint Recognition : Transfer Learning and Fine-Tuning Approaches
Author
Cheyma Nadir
Publisher
Globeedit
Publication year
2026
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6630119401
ISBN 13
9786630119404
Item weight
143 grams
Dimensions
220x150x6 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

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