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    Listar por autor "Thurnhofer-Hemsi, Karl"

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    Mostrando ítems 1-20 de 32

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      • A fast robust geometric fitting method for parabolic curves. 

        López-Rubio, EzequielAutoridad Universidad de Málaga; Thurnhofer-Hemsi, Karl; Blázquez-Parra, Elidia BeatrizAutoridad Universidad de Málaga; De-Cózar-Macías, ÓscarAutoridad Universidad de Málaga; Ladrón-de-Guevara-Muñoz, María del CarmenAutoridad Universidad de Málaga (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 LuisAutoridad Universidad de Málaga; Dávila-Arias, María GuadalupeAutoridad Universidad de Málaga[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, EnriqueAutoridad Universidad de Málaga (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, DomingoAutoridad Universidad de Málaga; Thurnhofer-Hemsi, Karl; Luque-Baena, Rafael MarcosAutoridad Universidad de Málaga; Jiménez Valverde, Clara; López-Rubio, EzequielAutoridad Universidad de Málaga[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 ÁngelAutoridad Universidad de Málaga; Thurnhofer-Hemsi, Karl; Molina Cabello, David; Palomo-Ferrer, Esteban JoséAutoridad Universidad de Málaga (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 LuisAutoridad Universidad de Málaga; Torres-Prioris, María José; López-Barroso, Diana; Thurnhofer-Hemsi, Karl; Paredes-Pacheco, José; Roé Vellvé, Núria; Alfaro, Francisco; Pertierra, Lucía; Dávila-Arias, María GuadalupeAutoridad Universidad de Málaga[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 ÁngelAutoridad Universidad de Málaga; López-Rubio, EzequielAutoridad Universidad de Málaga; Luque-Baena, Rafael MarcosAutoridad Universidad de Málaga; 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 ÁngelAutoridad Universidad de Málaga; Thurnhofer-Hemsi, Karl; Palomo-Ferrer, Esteban JoséAutoridad Universidad de Málaga; Rodríguez Capitán, Jorge; Molina Ramos, Ana Isabel; Jiménez-Navarro, Manuel FranciscoAutoridad Universidad de Málaga[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 JoséAutoridad Universidad de Málaga; 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, EzequielAutoridad Universidad de Málaga; Roé-Vellvé, Núria; Molina-Cabello, Miguel ÁngelAutoridad Universidad de Málaga (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, EzequielAutoridad Universidad de Málaga; Domínguez, Enrique; Luque-Baena, Rafael MarcosAutoridad Universidad de Málaga; 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, EzequielAutoridad Universidad de Málaga; Blázquez-Parra, Elidia BeatrizAutoridad Universidad de Málaga; Ladrón-de-Guevara-Muñoz, María del CarmenAutoridad Universidad de Málaga; De-Cózar-Macías, ÓscarAutoridad Universidad de Málaga (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 ÁngelAutoridad Universidad de Málaga; Thurnhofer-Hemsi, Karl; López-Rubio, EzequielAutoridad Universidad de Málaga[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 PilarAutoridad Universidad de Málaga; 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 ÁngelAutoridad Universidad de Málaga; Thurnhofer-Hemsi, Karl; Domínguez, Enrique; López-Rubio, EzequielAutoridad Universidad de Málaga; Palomo-Ferrer, Esteban JoséAutoridad Universidad de Málaga (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, EzequielAutoridad Universidad de Málaga; Roé-Vellvé, Núria; Molina-Cabello, Miguel ÁngelAutoridad Universidad de Málaga (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 ÁngelAutoridad Universidad de Málaga; López-Rubio, EzequielAutoridad Universidad de Málaga; Luque-Baena, Rafael MarcosAutoridad Universidad de Málaga; 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 ÁngelAutoridad Universidad de Málaga; Accino, Cristian; López-Rubio, EzequielAutoridad Universidad de Málaga; 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, EzequielAutoridad Universidad de Málaga; Domínguez, Enrique; Luque-Baena, Rafael MarcosAutoridad Universidad de Málaga; Molina-Cabello, Miguel ÁngelAutoridad Universidad de Málaga (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 ...
        REPOSITORIO INSTITUCIONAL UNIVERSIDAD DE MÁLAGA
        REPOSITORIO INSTITUCIONAL UNIVERSIDAD DE MÁLAGA
         

         

        REPOSITORIO INSTITUCIONAL UNIVERSIDAD DE MÁLAGA
        REPOSITORIO INSTITUCIONAL UNIVERSIDAD DE MÁLAGA