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pro vyhledávání: '"Raquel Esperanza Patino Escarcina"'
Publikováno v:
Pattern Recognition and Artificial Intelligence ISBN: 9783031090363
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c7cf8484075c9c123a3a62d67d14e565
https://doi.org/10.1007/978-3-031-09037-0_36
https://doi.org/10.1007/978-3-031-09037-0_36
Publikováno v:
IEEE Colombian Conference on Communication and Computing (IEEE COLCOM 2015).
The Content-based image retrieval (CBIR) systems and their application in different areas of development, are current research topics, however many of this systems are likely to fail due to use global features which cannot sufficiently capture the im
Autor:
Raquel Esperanza Patino Escarcina, Cesar Beltran Castanon, Roxana Flores-Quispe, Yuber Velazco-Paredes
Publikováno v:
SCCC
In order to identify the parasitic diseases, this paper propose the automatic identification of Human Parasite Eggs to eight different species: Ascaris, Uncinarias, Trichuris, Dyphillobothrium-Pacificum, Taenia-Solium, Fasciola Hepáticaand Enterobiu
Autor:
Yuber Velazco-Paredes, Roxana Flores-Quispe, Raquel Esperanza Patino Escarcina, Cesar Beltran Castanon
Publikováno v:
2014 IEEE Colombian Conference on Communications and Computing (COLCOM).
Publikováno v:
HIS
Clustering is an unsupervised classification method that divides a data set in groups, where the elements of a group have similar characteristics to each other. A well-known clustering method is the Growing Hierarchical Self-Organizing Map (GH-SOM),
Autor:
July Diana Banda Tapia, Raquel Esperanza Patino Escarcina, Monika N. Lopez Paredes, Dennis Barrios-Aranibar, Sonia Castelo Quispe
Publikováno v:
HIS
The usual method for classification processes of brazil-nut is manual and present some drawbacks like slowness, subjectivity, and inconsistency. In this paper, the main objective is to automate the classification process by analysing digital images w