Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Raul E. Gutierrez"'
We introduce CNER, an ensemble of capable tools for extraction of semantic relationships between named entities in Spanish language. Built upon a container-based architecture, CNER integrates different Named entity recognition and relation extraction
Externí odkaz:
http://arxiv.org/abs/2405.10485
Publikováno v:
2021 XLVII Latin American Computing Conference (CLEI).
Autor:
Raul E. Gutierrez, Ivana Matanovic, Maciej P. Polak, Ryan S. Johnson, Dane Morgan, Edl Schamiloglu
Publikováno v:
2021 22nd International Vacuum Electronics Conference (IVEC).
Publikováno v:
2020 IEEE 21st International Conference on Vacuum Electronics (IVEC).
Suppressing the harmful multipactor effect by, for instance, reducing secondary electron yield (SEY) is crucial in the design of RF space technologies. Therefore, improving fundamental understanding of how structural and electronic features of materi
Publikováno v:
2020 IEEE 21st International Conference on Vacuum Electronics (IVEC).
Secondary electron yield of a material is a crucial factor in designing many electronic devices, from electron multipliers to high-power radio frequency devices used in the aerospace industry. In the latter, it is key in mitigating the highly destruc
Publikováno v:
Journal of Applied Physics. 129:175105
Secondary electron yield (SEY) is relevant for widely used characterization methods (e.g., secondary electron spectroscopy and electron microscopy) and materials applications (e.g., multipactor effect). Key quantities necessary for understanding the
Publikováno v:
Información tecnológica v.29 n.3 2018
SciELO Chile
CONICYT Chile
instacron:CONICYT
SciELO Chile
CONICYT Chile
instacron:CONICYT
espanolEsta investigacion tiene como objetivo evaluar el riesgo laboral por estres termico en los trabajadores de los procesos de incineracion y secado en la empresa Arboriente S.A. Se trata de un estudio de campo, de tipo descriptivo y que se encuen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::611e5c04d36940b097fc3d4f26ce4a28
http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-07642018000300133
http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-07642018000300133
Publikováno v:
Cuadernos de Lingüística Hispánica, Iss 39, Pp 1-16 (2022)
La traducción automática (TA) se utiliza para obtener corpus anotados a partir de corpus provenientes del idioma inglés, los cuales pueden ser aplicables a diferentes tareas de procesamiento de lenguaje natural (PLN). Teniendo en cuenta que existe
Externí odkaz:
https://doaj.org/article/ad76b356a0c64085b23a60adec0315e3
Publikováno v:
TecnoLógicas, Vol 22, Pp 49-62 (2019)
In this article, we study the relation extraction problem from Natural Language Processing (NLP) implementing a domain adaptation setting without external resources. We trained a Deep Learning (DL) model for Relation Extraction (RE), which extracts s
Externí odkaz:
https://doaj.org/article/f0ba066c186641b890601db0d5cc47a3