Machine learning applications for mobile devices

Kód výsledku v 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>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Machine learning applications for mobile devices

Popis výsledku v původním jazyce

Research background: This paper explores and compares the possibilities of creating machine-to-machine applications for mobile devices. In today&apos;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 &amp; 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.

Název v anglickém jazyce

Machine learning applications for mobile devices

Popis výsledku anglicky

Research background: This paper explores and compares the possibilities of creating machine-to-machine applications for mobile devices. In today&apos;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 &amp; 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.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

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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Počet stran výsledku

7

Strana od-do

1-7

Název nakladatele

Žilinská univerzita

Místo vydání

Žilina

Místo konání akce

Rajecké Teplice

Datum konání akce

7. 10. 2015

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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