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Listar por autor "Thurnhofer-Hemsi, Karl"
Mostrando ítems 1-20 de 32
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A fast robust geometric fitting method for parabolic curves.
López-Rubio, Ezequiel; Thurnhofer-Hemsi, Karl; Blázquez-Parra, Elidia Beatriz
; De-Cózar-Macías, Óscar
; Ladrón-de-Guevara-Muñoz, María del Carmen
(Elsevier, 2018-07-18)
Fitting discrete data obtained by image acquisition devices to a curve is a common task in many fields of science and engineering. In particular, the parabola is some of the most employed shape features in electrical ... -
A reappraisal of echolalia in aphasia: A case-series study with multimodal neuroimaging
López-Barroso, Diana; Torres-Prioris, María José; Roé-Vellvé, Núria; Thurnhofer-Hemsi, Karl; Paredes-Pacheco, José; López-González, Francisco Javier; Tubío, Javier; Alfaro Rubio, Francisco; Berthier-Torres, Marcelo Luis; Dávila-Arias, María Guadalupe
[et al.] (2017-02-03)
Introduction: Verbal echoes are commonplace in patients with aphasia, yet information on their cognitive and neural mechanisms remains unexplored (Berthier et al., in press). This study aims to instantiate the concept ... -
Analysis and recognition of human gait activity based on multimodal sensors
Teran-Pineda, Diego; Thurnhofer-Hemsi, Karl; Domínguez-Merino, Enrique(MDPI, 2023-03-22)
Remote health monitoring plays a significant role in research areas related to medicine, neurology, rehabilitation, and robotic systems. These applications include Human Activity Recognition (HAR) using wearable sensors, ... -
Analysis of functional connectome pipelines for the diagnosis of autism spectrum disorders
Maza Quiroga, Rosa María; López-Rodríguez, Domingo; Thurnhofer-Hemsi, Karl; Luque-Baena, Rafael Marcos
; Jiménez Valverde, Clara; López-Rubio, Ezequiel
[et al.] (2022-05)
This paper explores the effect of using different pipelines to compute connectomes (matrices representing brain connections) and use them to train machine learning models with the goal of diagnosing Autism Spectrum ... -
Are learning styles useful? A new software to analyze correlations with grades and a case study in engineering
Molina-Cabello, Miguel Ángel; Thurnhofer-Hemsi, Karl; Molina Cabello, David; Palomo-Ferrer, Esteban José
(Wiley, 2023)
Knowing student learning styles represents an effective way to design the most suitable methodology for our students so that performance can improve with less effort for both students and teachers. However, a methodology ... -
Are you a doctor? … Are you a doctor? I’m not a doctor! A reappraisal of mitigated echolalia in aphasia with evaluation of neural correlates and treatment approaches.
Berthier-Torres, Marcelo Luis; Torres-Prioris, María José; López-Barroso, Diana; Thurnhofer-Hemsi, Karl; Paredes-Pacheco, José; Roé Vellvé, Núria; Alfaro, Francisco; Pertierra, Lucía; Dávila-Arias, María Guadalupe
[et al.] (Taylor & Francis, 2017-01)
Background: Mitigated echolalia (ME), a symptom of aphasia, involves deliberate repetition of just-heard words or phrases, possibly to aid auditory comprehension. Its functional basis remains largely unexplored. Aims: ... -
Blood Cell Classification Using the Hough Transform and Convolutional Neural Networks
Molina-Cabello, Miguel Ángel; López-Rubio, Ezequiel
; Luque-Baena, Rafael Marcos
; Rodríguez-Espinosa, María Jesús; Thurnhofer-Hemsi, Karl (Springer, 2018)
The detection of red blood cells in blood samples can be crucial for the disease detection in its early stages. The use of image processing techniques can accelerate and improve the effectiveness and efficiency of this ... -
CADICA: A new dataset for coronary artery disease detectionby using invasive coronary angiograph
Jiménez-Partinen, Ariadna; Molina-Cabello, Miguel Ángel; Thurnhofer-Hemsi, Karl; Palomo-Ferrer, Esteban José
; Rodríguez Capitán, Jorge; Molina Ramos, Ana Isabel; Jiménez-Navarro, Manuel Francisco
[et al.] (Wiley, 2024)
Coronary artery disease (CAD) remains the leading cause of death globally and invasive coronary angiography (ICA) is considered the gold standard of anatomical imaging evaluation when CAD is suspected. However, risk ... -
Deep learning for coronary artery disease severity classification
Jiménez-Partinen, Ariadna; Thurnhofer-Hemsi, Karl; Palomo-Ferrer, Esteban José; Molina-Ramos, Ana I. (2023)
Medical imaging evaluations are one of the fields where computed-aid diagnosis could improve the efficiency of diagnosis supporting physician decisions. Cardiovascular Artery Disease (CAD) is diagnosed using the gold ... -
Deep Learning networks with p-norm loss layers for spatial resolution enhancement of 3D medical images
Thurnhofer-Hemsi, Karl; López-Rubio, Ezequiel; Roé-Vellvé, Núria; Molina-Cabello, Miguel Ángel
(2019-06-19)
Nowadays, obtaining high-quality magnetic resonance (MR) images is a complex problem due to several acquisition factors, but is crucial in order to perform good diagnostics. The enhancement of the resolution is a typical ... -
Deep learning-based super-resolution of 3D magnetic resonance images by regularly spaced shifting
Thurnhofer-Hemsi, Karl; López-Rubio, Ezequiel; Domínguez, Enrique; Luque-Baena, Rafael Marcos
; Roé-Vellvé, Núria (Elsevier, 2020-07-20)
The image acquisition process in the field of magnetic resonance imaging (MRI) does not always provide high resolution results that may be useful for a clinical analysis. Super-resolution (SR) techniques manage to increase ... -
Desarrollo de un clasificador visual de especies de aves mediante redes neuronales convolucionales
Pérez Segarra, Antonio Miguel (2020-01-16)Se ha desarrollado un clasificador visual de especies de aves mediante redes neuronales convolucionales, en lenguaje Python haciendo uso de la libreríaa Keras. Se dispone de un conjunto de datos de 5771 imágenes repartidas ... -
Ellipse fitting by spatial averaging of random ensembles
Thurnhofer-Hemsi, Karl; López-Rubio, Ezequiel; Blázquez-Parra, Elidia Beatriz
; Ladrón-de-Guevara-Muñoz, María del Carmen
; De-Cózar-Macías, Óscar
(Elsevier, 2020-05)
Earlier ellipse fitting methods often consider the algebraic and geometric forms of the ellipse. The work presented here makes use of an ensemble to provide better results. The method proposes a new ellipse parametrization ... -
Encoding generative adversarial networks for defense against image classification attacks
Rodríguez Rodríguez, José Antonio; Pérez Bravo, José María; García-González, Jorge; Molina-Cabello, Miguel Ángel; Thurnhofer-Hemsi, Karl; López-Rubio, Ezequiel
[et al.] (2022)
Image classification has undergone a revolution in recent years due to the high performance of new deep learning models. However, severe security issues may impact the performance of these systems. In particular, adversarial ... -
Innovations that empower teachers: the case of i-Spring to design tailor-made learning materials.
Montijano-Cabrera, María del Pilar; Jiménez-Partinen, Ariadna; Thurnhofer-Hemsi, Karl; Fernández-Rodríguez, Jose David (2023)
Organizations must acknowledge the necessity of change and adopt diverse management strategies to swiftly adapt to the evolving technology and the new knowledge landscape. In the context of educational changes, an increasing ... -
Longitudinal study of the learning styles evolution in Engineering degrees
Molina-Cabello, Miguel Ángel; Thurnhofer-Hemsi, Karl; Domínguez, Enrique; López-Rubio, Ezequiel
; Palomo-Ferrer, Esteban José
(2021)
A learning style describes what are the predominant skills for learning tasks. In the context of university education, knowing the learning styles of the students constitutes a great opportunity to improve both teaching ... -
Multiobjective optimization of deep neural networks with combinations of Lp-norm cost functions for 3D medical image super-resolution
Thurnhofer-Hemsi, Karl; López-Rubio, Ezequiel; Roé-Vellvé, Núria; Molina-Cabello, Miguel Ángel
(IOS Press, 2020-05-20)
In medical imaging, the lack of high-quality images is present in many areas such as magnetic resonance (MR). Due to many acquisition impediments, the generated images have not enough resolution to carry out an adequate ... -
Neural Controller for PTZ cameras based on nonpanoramic foreground detection
Molina-Cabello, Miguel Ángel; López-Rubio, Ezequiel
; Luque-Baena, Rafael Marcos
; Domínguez, Enrique; Thurnhofer-Hemsi, Karl (2017-05-29)
Abstract—In this paper a controller for PTZ cameras based on an unsupervised neural network model is presented. It takes advantage of the foreground mask generated by a nonparametric foreground detection subsystem. Thus, ... -
Optimization of Convolutional Neural Network ensemble classifiers by Genetic Algorithms
Molina-Cabello, Miguel Ángel; Accino, Cristian; López-Rubio, Ezequiel
; Thurnhofer-Hemsi, Karl (Springer, 2019)
Breast cancer exhibits a high mortality rate and it is the most invasive cancer in women. An analysis from histopathological images could predict this disease. In this way, computational image processing might support this ... -
Panorama Construction for PTZ Camera Surveillance with the Neural Gas network
Thurnhofer-Hemsi, Karl; López-Rubio, Ezequiel; Domínguez, Enrique; Luque-Baena, Rafael Marcos
; Molina-Cabello, Miguel Ángel
(Wiley, 2018-04)
The construction of a model of the background of a scene still remains as a challenging task in video surveillance systems, in particular for moving cameras. This work presents a novel approach for constructing a panoramic ...