Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Lorena De Los Angeles Guachi"'
Autor:
Michele Bici, Francesco Gherardini, Lorena de Los Angeles Guachi-Guachi, Robinson Guachi, Francesca Campana
Publikováno v:
Advances on Mechanics, Design Engineering and Manufacturing IV ISBN: 9783031159275
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd3f9ba585e4c91c649b120592e12293
https://doi.org/10.1007/978-3-031-15928-2_68
https://doi.org/10.1007/978-3-031-15928-2_68
Autor:
Franz Paul Guzman, Ronny Velastegui, Carlos Enrique Bustamante, Jonathan David Freire, Hector Andres Mejia, Jordan Rodrigo Montenegro, Lorena De Los Angeles Guachi
Publikováno v:
DSDE
The COVID-19 pandemic has had a “devastating” impact on public health and well-being around the world. Early diagnosis is a crucial step to begin treatment and prevent more infections. In this sense, early screening approaches have demonstrated t
Autor:
Bryan Patricio Chachalo Gómez, Saravana Prakash Thirumuruganandham, Erik Solis, Eddy Andrade, Lorena de los Angeles Guachi Guachi, N.L. Parthasarathi, Robinson Guachi, Santiago Pozo Ruiz
Publikováno v:
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications ISBN: 9783030339036
CIARP
CIARP
In this paper, we present a new algorithm based on Computer-Aided Diagnosis (CAD) to detect breast cancer using digitized mammogram images. Here, we use image processing to make the pre-processing step of the images before we enter them into the clas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31b30f87244db63d6836d6ab641d66fe
https://doi.org/10.1007/978-3-030-33904-3_32
https://doi.org/10.1007/978-3-030-33904-3_32
Autor:
Pasquale Corsonello, Fabio Frustaci, Stefania Perri, Lorena-de-los-Angeles Guachi-Guachi, Giuseppe Cocorullo
Publikováno v:
Journal of Real-Time Image Processing. 16:1407-1423
In many computer vision systems, background subtraction algorithms have a crucial importance to extract information about moving objects. Although color features have been extensively used in several background subtraction algorithms, demonstrating h