Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/114113
Campo DC Valoridioma
dc.contributor.authorNeris Tomé, Roménen_US
dc.contributor.authorGuerra, Raelen_US
dc.contributor.authorLopez, Sebastianen_US
dc.contributor.authorSarmiento, Robertoen_US
dc.date.accessioned2022-03-21T09:26:41Z-
dc.date.available2022-03-21T09:26:41Z-
dc.date.issued2021en_US
dc.identifier.isbn9781665421164en_US
dc.identifier.otherScopus-
dc.identifier.urihttp://hdl.handle.net/10553/114113-
dc.description.abstractOver the last few years, Convolutional Neural Networks (CNNs) have been extensively used in different remote sensing applications. However, for large networks the computation and memory requirements have brought many challenges into this field. Additionally, the computational capabilities of hardware devices available on-board satellites is limited, being this another constraint for these implementations. In this paper, the authors present the evaluation of nine different CNN architectures for ship and airplane detection, taking into consideration that the final use-case application will be an on-board system with target detection capabilities.en_US
dc.languageengen_US
dc.relation.ispartofProceedings (Conference on Design of Circuits and Integrated Systems)en_US
dc.source36th Conference on Design of Circuits and Integrated Systems, DCIS 2021 [EISSN 2640-5563], (Enero 2021)en_US
dc.subject3307 Tecnología electrónicaen_US
dc.subject.otherDeep Learningen_US
dc.subject.otherMachine Learningen_US
dc.subject.otherNeural Networksen_US
dc.subject.otherRemote Sensingen_US
dc.subject.otherTarget Detectionen_US
dc.titlePerformance evaluation of state-of-The-Art CNN architectures for the on-board processing of remotely sensed imagesen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conference36th Conference on Design of Circuits and Integrated Systems - DCIS 2021en_US
dc.identifier.doi10.1109/DCIS53048.2021.9666179en_US
dc.identifier.scopus85124965294-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.authorscopusid55812965200-
dc.contributor.authorscopusid57459706600-
dc.contributor.authorscopusid57187722000-
dc.contributor.authorscopusid35609452100-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.utils.revisionen_US
dc.date.coverdateEnero 2021en_US
dc.identifier.conferenceidevents130120-
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-TELen_US
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.author.deptGIR IUMA: Diseño de Sistemas Electrónicos Integrados para el procesamiento de datos-
crisitem.author.deptIU de Microelectrónica Aplicada-
crisitem.author.deptDepartamento de Ingeniería Electrónica y Automática-
crisitem.author.deptGIR IUMA: Diseño de Sistemas Electrónicos Integrados para el procesamiento de datos-
crisitem.author.deptIU de Microelectrónica Aplicada-
crisitem.author.deptDepartamento de Ingeniería Electrónica y Automática-
crisitem.author.orcid0000-0002-5033-9809-
crisitem.author.orcid0000-0002-2360-6721-
crisitem.author.orcid0000-0002-4843-0507-
crisitem.author.parentorgIU de Microelectrónica Aplicada-
crisitem.author.parentorgIU de Microelectrónica Aplicada-
crisitem.author.fullNameNeris Tomé, Romén-
crisitem.author.fullNameLópez Suárez, Sebastián Miguel-
crisitem.author.fullNameSarmiento Rodríguez, Roberto-
Colección:Actas de congresos
Vista resumida

Citas SCOPUSTM   

2
actualizado el 24-mar-2024

Visitas

32
actualizado el 17-jun-2023

Google ScholarTM

Verifica

Altmetric


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.