Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Juan Manuel Ramos Arreguín"'
Publikováno v:
Nova Scientia, Vol 15, Iss 31 (2023)
Traffic accidents are one of the main causes of death in Mexico, the collisions are caused mostly due to human error, therefore attempts have been made to reduce these shortcomings with driver assistance systems. This paper presents a study conducted
Externí odkaz:
https://doaj.org/article/20999862adcb452b941aa75491eb3ed3
Autor:
Juan Carlos Moya Morales, Juan Carlos Pedraza Ortega, Juan Manuel Ramos Arreguín, Marco Antonio Aceves Fernández, Efrén Gorrostieta Hurtado
Publikováno v:
Programación Matemática y Software, Vol 10, Iss 2 (2018)
En el presente trabajo se muestra la comparación realizada del método de Perfilometría por Transformada de Fourier. Utilizando en primer lugar laTrasformada de Fourier Unidimensional y posteriormente la Transformada de Fourier Bidimensional, ambas
Externí odkaz:
https://doaj.org/article/516066aa2d5947c792e2582113464684
Autor:
Luis-Rogelio Roman-Rivera, Israel Sotelo-Rodríguez, Jesus Carlos Pedraza-Ortega, Marco Antonio Aceves-Fernandez, Juan Manuel Ramos-Arreguín, Efrén Gorrostieta-Hurtado
Publikováno v:
Mathematics, Vol 10, Iss 12, p 2085 (2022)
RGB-D cameras produce depth and color information commonly used in the 3D reconstruction and vision computer areas. Different cameras with the same model usually produce images with different calibration errors. The color and depth layer usually requ
Externí odkaz:
https://doaj.org/article/cc800563f6cf4ee68ddd76711a82877e
Autor:
Sebastián Salazar-Colores, Juan-Manuel Ramos-Arreguín, Jesús-Carlos Pedraza-Ortega, J Rodríguez-Reséndiz
Publikováno v:
EURASIP Journal on Image and Video Processing, Vol 2019, Iss 1, Pp 1-8 (2019)
Abstract Outdoor images can be degraded due to the particles in the air that absorb and scatter light. The produced degradation generates contrast attenuation, blurring, and distortion in pixels, resulting in low visibility. These limit the efficienc
Externí odkaz:
https://doaj.org/article/c1bf4dcf4ce2423f8a24005a9de9fda5
Autor:
Marco-Antonio Cabrera-Rufino, Juan-Manuel Ramos-Arreguín, Juvenal Rodríguez-Reséndiz, Efren Gorrostieta-Hurtado, Marco-Antonio Aceves-Fernandez
Publikováno v:
Micromachines; Volume 13; Issue 6; Pages: 890
Artificial intelligence techniques for pneumatic robot manipulators have become of deep interest in industrial applications, such as non-high voltage environments, clean operations, and high power-to-weight ratio tasks. The principal advantages of th
Autor:
Luis-Rogelio Roman-Rivera, Jesus Carlos Pedraza-Ortega, Marco Antonio Aceves-Fernandez, Juan Manuel Ramos-Arreguín, Efrén Gorrostieta-Hurtado, Saúl Tovar-Arriaga
Publikováno v:
Mathematics
Volume 11
Issue 4
Pages: 1023
Volume 11
Issue 4
Pages: 1023
Three-dimensional vision cameras, such as RGB-D, use 3D point cloud to represent scenes. File formats as XYZ and PLY are commonly used to store 3D point information as raw data, this information does not contain further details, such as metadata or s
Autor:
Mariano Garduño Aparicio, Juan Manuel Ramos Arreguín, Eduardo Ulises Moya Sánchez, Sebastián Salazar Colores, Claudia Victoria Lopez Torres
Publikováno v:
Computación y Sistemas. 23
Non-uniform illumination is a common issue in images acquired in uncontrolled environments. Elimination or reduction of the non-uniform illumination problem is required in order to get an accurate image binarization. This paper introduces the combina
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Autor:
Osmar Antonio Espinosa-Bernal, Jesús Carlos Pedraza-Ortega, Marco Antonio Aceves-Fernandez, Victor Manuel Martínez-Suárez, Saul Tovar-Arriaga, Juan Manuel Ramos-Arreguín, Efrén Gorrostieta-Hurtado
Publikováno v:
Computers, Vol 13, Iss 6, p 145 (2024)
The modeling of real objects digitally is an area that has generated a high demand due to the need to obtain systems that are able to reproduce 3D objects from real objects. To this end, several techniques have been proposed to model objects in a com
Externí odkaz:
https://doaj.org/article/81ad9b0d2b5d422491ea02869532ac9c
Autor:
Enrique Mena-Camilo, Sebastián Salazar-Colores, Marco Antonio Aceves-Fernández, Edgard Efrén Lozada-Hernández, Juan Manuel Ramos-Arreguín
Publikováno v:
Diagnostics, Vol 14, Iss 12, p 1278 (2024)
This paper introduces a novel one-dimensional convolutional neural network that utilizes clinical data to accurately detect choledocholithiasis, where gallstones obstruct the common bile duct. Swift and precise detection of this condition is critical
Externí odkaz:
https://doaj.org/article/8235f77a1be54b2390154e8d0b21dfde