Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Erick Gomez Nieto"'
Autor:
Daniel A. Gutierrez-Pachas, Germain Garcia-Zanabria, Ernesto Cuadros-Vargas, Guillermo Camara-Chavez, Erick Gomez-Nieto
Publikováno v:
Education Sciences, Vol 13, Iss 2, p 154 (2023)
The prediction of university dropout is a complex problem, given the number and diversity of variables involved. Therefore, different strategies are applied to understand this educational phenomenon, although the most outstanding derive from the join
Externí odkaz:
https://doaj.org/article/f9e9cfd09a8c41fa852a5f5f627b6ea4
Autor:
Germain Garcia-Zanabria, Daniel A. Gutierrez-Pachas, Guillermo Camara-Chavez, Jorge Poco, Erick Gomez-Nieto
Publikováno v:
Applied Sciences, Vol 12, Iss 12, p 5785 (2022)
High and persistent dropout rates represent one of the biggest challenges for improving the efficiency of the educational system, particularly in underdeveloped countries. A range of features influence college dropouts, with some belonging to the edu
Externí odkaz:
https://doaj.org/article/37b73ab1fb614937be5d828748239e16
Autor:
Daniel A. Gutierrez-Pachas, Germain Garcia-Zanabria, Alex J. Cuadros-Vargas, Guillermo Camara-Chavez, Jorge Poco, Erick Gomez-Nieto
Publikováno v:
Education Sciences, Vol 12, Iss 4, p 242 (2022)
Computer science is a dynamic field of study that requires constant review and updating of the curricular designs in academic programs—in general, measuring the impact of plan changes has been little explored in the literature. In most cases, it fo
Externí odkaz:
https://doaj.org/article/3ed0115a3d6640458bbfe9db1d93869a
Publikováno v:
Sensors, Vol 22, Iss 5, p 1752 (2022)
Recognition using ear images has been an active field of research in recent years. Besides faces and fingerprints, ears have a unique structure to identify people and can be captured from a distance, contactless, and without the subject’s cooperati
Externí odkaz:
https://doaj.org/article/93571d3021a24be58090241df5d504a5
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f157b7f2787439a7f0e47bd2ec6d6925
https://doi.org/10.1016/j.cag.2022.02.005
https://doi.org/10.1016/j.cag.2022.02.005
Autor:
Marcos César Alvarez, Erick Gomez-Nieto, Gustavo Lucas Higa, Efraín García-Sánchez, Pedro Rolo Benetti
Publikováno v:
New Media & Society. 25:1130-1152
The aim of this research is to describe the pattern of interactions of Brazilian legislators on Twitter during 2019 in the construction of political discourses. Based on 20,076 replies during 2019, posted on Twitter by 514 Brazilian legislators, we c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a8307f9a22cb12273dee3fe83809f24b
https://doi.org/10.1177/14614448211017920
https://doi.org/10.1177/14614448211017920
Publikováno v:
Sensors; Volume 22; Issue 5; Pages: 1752
Recognition using ear images has been an active field of research in recent years. Besides faces and fingerprints, ears have a unique structure to identify people and can be captured from a distance, contactless, and without the subject’s cooperati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53844fcecfc545e99cda103c86f37d26
Autor:
Daniel A. Gutierrez Pachas, Germain Garcia-Zanabria, Alex J. Cuadros-Vargas, Guillermo Camara-Chavez, Jorge Poco, Erick Gomez-Nieto
Publikováno v:
2021 XLVII Latin American Computing Conference (CLEI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff2e93892d2b5b0f7926ccea6feaa491
https://doi.org/10.1109/clei53233.2021.9640119
https://doi.org/10.1109/clei53233.2021.9640119
Publikováno v:
2021 34th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::050b32cf4f58bf8b94fa8a67d63394d0
https://doi.org/10.1109/sibgrapi54419.2021.00027
https://doi.org/10.1109/sibgrapi54419.2021.00027
Publikováno v:
SAC
Clustering methods are the most used algorithms for unsupervised learning. However, there is no unique optimal approach for all datasets since different clustering algorithms produce different partitions. To overcome this issue of selecting an approp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c4b52632d886897de4fd0bad367d886
https://doi.org/10.1145/3412841.3441921
https://doi.org/10.1145/3412841.3441921