Migration of Artificial Neural Networks to Smartphones
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F20%3A50017104" target="_blank" >RIV/62690094:18450/20:50017104 - isvavai.cz</a>
Výsledek na webu
<a href="https://link.springer.com/chapter/10.1007/978-3-030-58799-4_61" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-58799-4_61</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-58799-4_61" target="_blank" >10.1007/978-3-030-58799-4_61</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Migration of Artificial Neural Networks to Smartphones
Popis výsledku v původním jazyce
The paper explains the process of migration of an artificial neural network (ANN) to a smartphone device. It focuses on a situation when the ANN is already deployed on a desktop computer. Our goal is to describe the process of the migration of the network to a mobile environment. In the current system we have, images have to be scanned and fed to a computer that is applying the ANN. However, every smartphone has a camera that can be used instead of a scanner. Migration to such a device should save the overall processing time. ANNs in the field of computer vision have a long history. Despite that, mobile phones were not used as a target platform for ANNs because they did not have enough processing power. In the past years, smartphones have developed dramatically, and they have the processing power necessary for deploying ANNs now. Also, major mobile operating systems, Android and iOS, have included the support for the deployment.
Název v anglickém jazyce
Migration of Artificial Neural Networks to Smartphones
Popis výsledku anglicky
The paper explains the process of migration of an artificial neural network (ANN) to a smartphone device. It focuses on a situation when the ANN is already deployed on a desktop computer. Our goal is to describe the process of the migration of the network to a mobile environment. In the current system we have, images have to be scanned and fed to a computer that is applying the ANN. However, every smartphone has a camera that can be used instead of a scanner. Migration to such a device should save the overall processing time. ANNs in the field of computer vision have a long history. Despite that, mobile phones were not used as a target platform for ANNs because they did not have enough processing power. In the past years, smartphones have developed dramatically, and they have the processing power necessary for deploying ANNs now. Also, major mobile operating systems, Android and iOS, have included the support for the deployment.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2020
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Computational Science and Its Applications – ICCSA 2020
ISBN
978-3-030-58798-7
ISSN
0302-9743
e-ISSN
1611-3349
Počet stran výsledku
14
Strana od-do
845-858
Název nakladatele
Springer Nature Switzerland AG 2020
Místo vydání
Springer, Cham
Místo konání akce
Cagliari, Italy
Datum konání akce
1. 7. 2020
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
—