Documentos de conferencia

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https://hdl.handle.net/10784/27881

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Examinando Documentos de conferencia por Materia "algorithm"

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    Efficient use of mobile devices for quantification of pressure injury images
    (IOS Press, 2018-01-01) Garcia-Zapirain B; Sierra-Sosa D; Ortiz P D; Isaza-Monsalve M; Elmaghraby A; Garcia-Zapirain B; Sierra-Sosa D; Ortiz P D; Isaza-Monsalve M; Elmaghraby A; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
    Pressure Injuries are chronic wounds that are formed due to the constriction of the soft tissues against bone prominences. In order to assess these injuries, the medical personnel carry out the evaluation and diagnosis using visual methods and manual measurements, which can be inaccurate and may generate discomfort in the patients. By using segmentation techniques, the Pressure Injuries can be extracted from an image and accurately parameterized, leading to a correct diagnosis. In general, these techniques are based on the solution of differential equations and the involved numerical methods are demanding in terms of computational resources. In previous work, we proposed a technique developed using toroidal parametric equations for image decomposition and segmentation without solving differential equations. In this paper, we present the development of a mobile application useful for the non-contact assessment of Pressure Injuries based on the toroidal decomposition from images. The usage of this technique allows us to achieve an accurate segmentation almost 8 times faster than Active Contours without Edges (ACWE) and Dynamic Contours methods.We describe the techniques and the implementation for Android devices using Python and Kivy. This application allows for the segmentation and parameterization of injuries, obtain relevant information for the diagnosis and tracking the evolution of patient's injuries. © 2018 - IOS Press and the authors.
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    Recognition and regionalization of emotions in the arousal-valence plane
    (Institute of Electrical and Electronics Engineers Inc., 2015-01-01) Bustamante, P.A.; Lopez Celani, N.M.; Perez, M.E.; Quintero Montoya, O.L.; Bustamante, P.A.; Lopez Celani, N.M.; Perez, M.E.; Quintero Montoya, O.L.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
    The emotion recognition systems have become important for the diversity of its applications. Several methodologies have been proposed based on how emotions are reflected in biological systems, such as facial expressions, the activity of the nervous system or the prosody of voice. The detection of emotions by voice processing is an approach that involves a noninvasive procedure that produces results with an acceptable rate of detection. In this work an algorithm for features extraction was developed, that efficiently classify different emotional states. Thus, emotions that have not been trained can be associated with a trained emotion both belonging to the same region of the valence-arousal plane.