Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Camilo Andrés Pulido-Rojas"'
Publikováno v:
Revista Facultad de Ingeniería Universidad de Antioquia, Iss 80, Pp 124-130 (2016)
El presente trabajo expone un sistema de visión de máquina para la detección de maleza en cultivos de hortalizas, usando imágenes exteriores, evadiendo problemas de iluminación y nitidez durante la etapa de adquisición, ya que el presente desar
Externí odkaz:
https://doaj.org/article/4a6ef2be523243b098fcbd475a736205
Publikováno v:
Ingeniería e Investigación, Vol 37, Iss 1, Pp 68-74 (2017)
Repositorio UN
Universidad Nacional de Colombia
instacron:Universidad Nacional de Colombia
Repositorio UN
Universidad Nacional de Colombia
instacron:Universidad Nacional de Colombia
This paper presents a classification system for weeds and vegetables from outdoor crop images. The classifier is based on support vector machine (SVM) with its extension to nonlinear case using radial basis function (RBF) and optimizing its scale par
Autor:
Manuel Alejandro Molina Villa, Camilo Andrés Pulido Rojas, Leonardo Enrique Solaque Guzmán, Daniel Ricardo Avendaño Flórez, Nelson Fernando Velasco Toledo
Publikováno v:
Revista UIS Ingenierías, Vol 15, Iss 2 (2016)
Robot operating system (ROS) provides algorithms and services to control different kind of robots. ROS is a useful tool in many issues in the field of autonomous robots, especially in applications as mapping, localization and autonomous navigation in
Publikováno v:
Engineering Journal, Vol 21, Iss 2 (2017)
This paper exposes a comparative analysis of three weed classification strategies based on area and texture features over images of vegetable crops, focus on provide a technological tool to support farmers in their maintenance tasks. The classificati
Publikováno v:
2016 IEEE Colombian Conference on Robotics and Automation (CCRA).
This article on implementing a machine vision process, such as to enable support processes of agriculture. Work is born of the problems presented by different crops, causing great losses in both time and costs. Using machine vision every inconvenienc