Machine learning applications for mobile devices
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F22%3A39919639" target="_blank" >RIV/00216275:25530/22:39919639 - 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
Machine learning applications for mobile devices
Original language description
Research background: This paper explores and compares the possibilities of creating machine-to-machine applications for mobile devices. In today's globalized world, we encounter many areas where machine learning is suitable for various human activities. Machine learning helps organizations in analyzing the reality around us and one of the activities that machine learning deals with is the analysis of digital content and especially digital images.Purpose of the article: The aim of this paper is to bring new perspectives on the possibilities of creating machine learning applications for mobile phones. Currently, there are a large number of options for creating such an application, and not all of them are easy to understand or usable for practical applications.Methods: The methods used in the paper are mainly observation and surveys of existing papers. It is possible to use users’ local hardware and data to solve machine learning problems on mobile devices and paper show some possibilities, advantages, disadvantages and challenges that are connected with this phenomena.Findings & Value added: Machine learning applications are currently on the rise, as there are an ever-increasing number of opportunities to use these applications. There is also an ever-increasing number of different libraries and SDKs for creating such applications. The contribution of this paper is then to compare the different libraries and another contribution is to find out how such applications can be used and more importantly created.
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
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Zborník abstraktov z medzinárodnej vedeckej konferencie Globalizácia a jej sociálno - ekonomické dôsledky ´15
ISBN
978-80-554-1102-6
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
1-7
Publisher name
Žilinská univerzita
Place of publication
Žilina
Event location
Rajecké Teplice
Event date
Oct 7, 2015
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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