Aviso: para depositar documentos, por favor, inicia sesión e identifícate con tu cuenta de correo institucional de la UCM con el botón MI CUENTA UCM. No emplees la opción AUTENTICACIÓN CON CONTRASEÑA
 

Analysis of Machine Learning Techniques for Information Classification in Mobile Applications

dc.contributor.authorPérez Arteaga, Sandra
dc.contributor.authorSandoval Orozco, Ana Lucila
dc.contributor.authorGarcía Villalba, Luis Javier
dc.date.accessioned2024-11-18T15:41:29Z
dc.date.available2024-11-18T15:41:29Z
dc.date.issued2023-04-27
dc.description2023 Descuento MDPI
dc.description.abstractDue to the daily use of mobile technologies, we live in constant connection with the world through the Internet. Technological innovations in smart devices have allowed us to carry out everyday activities such as communicating, working, studying or using them as a means of entertainment, which has led to smartphones displacing computers as the most important device connected to the Internet today, causing users to demand smarter applications or functionalities that allow them to meet their needs. Artificial intelligence has been a major innovation in information technology that is transforming the way users use smart devices. Using applications that make use of artificial intelligence has revolutionised our lives, from making predictions of possible words based on typing in a text box, to being able to unlock devices through pattern recognition. However, these technologies face problems such as overheating and battery drain due to high resource consumption, low computational capacity, memory limitations, etc. This paper reviews the most important artificial intelligence algorithms for mobile devices, emphasising the challenges and problems that can arise when implementing these technologies in low-resource devices.
dc.description.departmentDepto. de Ingeniería de Software e Inteligencia Artificial (ISIA)
dc.description.facultyFac. de Informática
dc.description.refereedTRUE
dc.description.sponsorshipEuropean Commission
dc.description.statuspub
dc.identifier.citationPérez Arteaga, S.; Sandoval Orozco, A.L.; García Villalba, L.J. Analysis of Machine Learning Techniques for Information Classification in Mobile Applications. Appl. Sci. 2023, 13, 5438. https://doi.org/10.3390/app13095438
dc.identifier.doi10.3390/app13095438
dc.identifier.issn2076-3417
dc.identifier.officialurlhttps://doi.org/10.3390/app13095438
dc.identifier.urihttps://hdl.handle.net/20.500.14352/110717
dc.issue.number5438
dc.journal.titleApplied Sciences
dc.language.isoeng
dc.page.final19
dc.page.initial1
dc.publisherMDPI
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/101021801/EU
dc.rightsAttribution 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject.keywordAlgorithms
dc.subject.keywordArchitectures
dc.subject.keywordArtificial intelligence
dc.subject.keywordChallenges
dc.subject.keywordClassification
dc.subject.keywordDeep learning
dc.subject.keywordFederated learning
dc.subject.keywordLimited resources
dc.subject.keywordMobile devices
dc.subject.ucmInformática (Informática)
dc.subject.unesco3399 Otras Especialidades Tecnológicas
dc.titleAnalysis of Machine Learning Techniques for Information Classification in Mobile Applications
dc.typejournal article
dc.type.hasVersionVoR
dc.volume.number13
dspace.entity.typePublication
relation.isAuthorOfPublicationb86e9167-5069-4838-86e6-a55613a5da72
relation.isAuthorOfPublicationdea44425-99a5-4fef-b005-52d0713d0e0d
relation.isAuthorOfPublication0f67f6b3-4d2f-4545-90e1-95b8d9f3e1f0
relation.isAuthorOfPublication.latestForDiscoveryb86e9167-5069-4838-86e6-a55613a5da72

Download

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
applsci.pdf
Size:
791.94 KB
Format:
Adobe Portable Document Format
Description:
Analysis of Machine Learning Techniques for Information Classification in Mobile Applications

Collections