Zobrazeno 1 - 7
of 7
pro vyhledávání: '"K. L. Ponce-Guevara"'
Publikováno v:
Neural Networks. 130:253-268
A surge in the availability of data from multiple sources and modalities is correlated with advances in how to obtain, compress, store, transfer, and process large amounts of complex high-dimensional data. The clustering challenge increases with the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::545cd21085d1f1b300e4d348ae9526ba
https://doi.org/10.1016/j.neunet.2020.06.022
https://doi.org/10.1016/j.neunet.2020.06.022
Autor:
Marcelo Zambrano-Vizuete, Marco Jimenez-Guevara, Jenyffer Yepez-Chicaiza, Mauricio Dominguez-Limaico, Edgar Maya-Olalla, K. L. Ponce-Guevara
Publikováno v:
Technology, Sustainability and Educational Innovation (TSIE) ISBN: 9783030372200
This research presents the design and implementation of a control system based on the registration of brain signals using EEG technology. It focused on support for people with physical-motor disability and is segmented in phases for its development a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dc09c093038cd593d21c7143567d321e
https://doi.org/10.1007/978-3-030-37221-7_22
https://doi.org/10.1007/978-3-030-37221-7_22
Publikováno v:
IJCNN
Inductive transfer learning is widespread in computer vision applications. However, in natural language processing (NLP) applications is still an under-explored area. The most common transfer learning method in NLP is the use of pre-trained word embe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::78ffa4d5ddefc8ac460d0c7aa1b1533d
https://doi.org/10.1109/ijcnn.2019.8852398
https://doi.org/10.1109/ijcnn.2019.8852398
Autor:
Diego Hernán Peluffo-Ordóñez, J. A. Riascos-Salas, J. A. Salazar-Castro, Omar R. Ona-Rocha, M. A. Páez-Jaime, I. C. Marrufo-Rodríguez, D. Mayorca-Torres, K. L. Ponce-Guevara
Publikováno v:
Communications in Computer and Information Science ISBN: 9783030366353
Time-varying data characterization and classification is a field of great interest in both scientific and technology communities. There exists a wide range of applications and challenging open issues such as: automatic motion segmentation, moving-obj
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa8611ed4f15aefd965d054faad12d5c
https://doi.org/10.1007/978-3-030-36636-0_3
https://doi.org/10.1007/978-3-030-36636-0_3
Autor:
Paul D. Rosero-Montalvo, José Luis Rodríguez-Sotelo, Israel David Herrera-Granda, Miguel A. Becerra, Andrés Eduardo Castro-Ospina, Leandro L. Lorente-Leyva, K. L. Ponce-Guevara, Diego Hernán Peluffo-Ordóñez
Publikováno v:
Advances in Neural Networks – ISNN 2018 ISBN: 9783319925363
ISNN
ISNN
Normalized-cut clustering (NCC) is a benchmark graph-based approach for unsupervised data analysis. Since its traditional formulation is a quadratic form subject to orthogonality conditions, it is often solved within an eigenvector-based framework. N
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae77d5e812d1c4bf78ba9e933a41222f
https://doi.org/10.1007/978-3-319-92537-0_37
https://doi.org/10.1007/978-3-319-92537-0_37
Autor:
Stefany Flores, Luis Suarez, Ana C. Umaquinga-Criollo, Paul D. Rosero-Montalvo, J. Pijal, A. Guzman, K. Moncayo, K. L. Ponce-Guevara, D. Lugo, D. Nejer
Publikováno v:
2017 International Conference on Information Systems and Computer Science (INCISCOS).
The present work presents an analysis of the neighborhood criterion for the prototype selection (PS) in supervised machine learning classification algorithms. To do this, we use the condensed neighbor algorithm CNN to eliminate redundant data with th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fb3a2c676aae2dafcc22ad1da308a25f
https://doi.org/10.1109/inciscos.2017.47
https://doi.org/10.1109/inciscos.2017.47
Autor:
Diego Hernán Peluffo-Ordóñez, Edgar Maya-Olalla, Juan C. Alvarado-Pérez, Hernán Domínguez-Limaico, K. L. Ponce-Guevara, J. A. Palacios-Echeverria, Luis Suárez-Zambrano, Paul D. Rosero-Montalvo
Publikováno v:
2017 IEEE Second Ecuador Technical Chapters Meeting (ETCM).
This work shows the use of Big Data and Data Mining techniques on vegetable crops data from a greenhouse by implementing the first version of a software tool, so called GreenFarm-DM. Such a tool is aimed at analyzing the factors that influence the gr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::75397a1a530ab908516f2878b9647dee
https://doi.org/10.1109/etcm.2017.8247519
https://doi.org/10.1109/etcm.2017.8247519