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Performance/resources comparison of hardware implementations on fully connected network inference
dc.contributor.author | Lozada, R. | |
dc.contributor.author | Ruiz, J. | |
dc.contributor.author | González, M. L. | |
dc.contributor.author | Sedano, J. | |
dc.contributor.author | Villar Flecha, José Ramón | |
dc.contributor.author | García Vico, Á. M. | |
dc.contributor.author | Skibinsky Gitlin, E. S. | |
dc.date.accessioned | 2023-05-18T08:22:02Z | |
dc.date.available | 2023-05-18T08:22:02Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Lozada, R., Ruiz, J., González, M. L., Sedano, J., Villar Flecha, J. R., García Vico, A. M., Skibinsky Gitlin, E. S. (2022). Performance/resources comparison of hardware implementations on fully connected network inference. En: H. Yin, D. Camacho, P. Tino (eds.). Intelligent data engineering and automated learning – IDEAL 2022 (pp. 348-358). Cham : Springer | |
dc.identifier.isbn | 9783031217524 | |
dc.identifier.issn | 0302-9743 | |
dc.identifier.uri | http://hdl.handle.net/10651/68163 | |
dc.description | Intelligent Data Engineering and Automated Learning – IDEAL 2022 (23rd. 2022. Manchester) | |
dc.description.sponsorship | This work has been founded by the following institutions: the Ministry of Science and Innovation under CERVERA Excellence Network project CER-20211003 (IBERUS), Missions Science and Innovation project MIG-20211008 (INMERBOT), European Union’s Horizon 2020 research and innovation programme (project DIH4CPS) under the Grant Agreement no 872548, CDTI (Centro para el Desarrollo Tecnológico Industrial) under projects CER-20211022, ICE (Junta de Castilla y León) under project CCTT3/20/BU/0002, the Spanish Ministry of Economics and Industry under the grant PID2020-112726RB-I00, the Principado de Asturias under the grant SV-PA-21-AYUD/2021/50994 and the Regional Government of Andalusia, program “Personal Investigador Doctor”, reference DOC_00235. | |
dc.format.extent | p. 348-358 | |
dc.language.iso | eng | |
dc.relation.ispartof | Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | |
dc.relation.ispartofseries | Lecture Notes in Computer Science book series (LNCS); v. 13756 | |
dc.rights | © 2022 The author(s), under exclusive license to Springer Nature Switzerland AG | |
dc.source | Scopus | |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144826188&doi=10.1007%2f978-3-031-21753-1_34&partnerID=40&md5=8c9d5a76485eb94cc313a5f006f44a5d | |
dc.title | Performance/resources comparison of hardware implementations on fully connected network inference | |
dc.type | conference output | spa |
dc.identifier.doi | 10.1007/978-3-031-21753-1_34 | |
dc.relation.projectID | MCIN/CER-20211003 | |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/872548 | |
dc.relation.projectID | MINECO/PID2020-112726RB-I00 | |
dc.relation.projectID | SV-PA-21-AYUD/2021/50994 | |
dc.relation.publisherversion | http://dx.doi.org/10.1007/978-3-031-21753-1_34 | |
dc.rights.accessRights | open access | |
dc.type.hasVersion | AM |
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