Convolutional neural networks in hand-based recognition system
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F19%3A39914417" target="_blank" >RIV/00216275:25410/19:39914417 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Convolutional neural networks in hand-based recognition system
Original language description
Biometric systems are often discussed today. Authentication systems that work with biometric data (such as fingerprint, iris, hand geometry) have a high level of security. There are many reasons why it is necessary to have a strong authentication system. One of them is the existence of information systems that store sensitive data that needs to be protected. This article is focused on hand-based identification systems. A typical hand-based authentication system performs: data acquisition, feature extraction, classification, and decision. This paper presents the use of a convolutional neural network to identify people based on hand geometry. Convolutional neural networks are used for pattern recognition. When using a convolutional neural network, it is not necessary before classification feature extraction. Experiments were performed on a database of 550 hand images from 114 people, each person provided 5 images. The accuracy of the identification of persons was 94.11%, 3 images of each person were used for training.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of 34th International Business Information Management Association Conference. Vision 2025: Education Excellence and Management of Innovations through Sustainable Economic Competitive Advantage, IBIMA 2019
ISBN
978-0-9998551-3-3
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
4744-4750
Publisher name
International Business Information Management Association-IBIMA
Place of publication
Norristown
Event location
Madrid
Event date
Nov 13, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000556337406043