Listar por autor "Thurnhofer-Hemsi, Karl"
Mostrando ítems 1-20 de 34
-
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 ... -
Analyzing Digital Image by Deep Learning for Melanoma Diagnosis
Thurnhofer Hemsi, Karl; Domínguez-Merino, Enrique (2019-06-19)
Image classi cation is an important task in many medical applications, in order to achieve an adequate diagnostic of di erent le- sions. Melanoma is a frequent kind of skin cancer, which most of them can be detected by ... -
Aprendizaje automático para la detección de inicio/fin de la marcha mediante dos sensores inerciales y modelado de datos usando aprendizaje profundo.
(UMA Editorial, 2024)Los médicos utilizan extensamente el análisis de la marcha para detectar anormalidades y determinar posibles tratamientos para los pacientes. El análisis de la marcha tiene diversas aplicaciones, que incluyen la identificación ... -
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 ... -
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 ... -
Comparación de marcos de trabajo de Aprendizaje Profundo para la detección de objetos
Benito-Picazo, Jesús; Thurnhofer Hemsi, Karl; Molina-Cabello, Miguel Ángel; Domínguez, Enrique (2018-11-08)
Muchas aplicaciones en visión por computador necesitan de sistemas de detección precisos y eficientes. Esta demanda coincide con el auge de la aplicación de técnicas de aprendizaje profundo en casi todos las áreas del ... -
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 ... -
Desarrollo de un clasificador visual de especies de aves mediante redes neuronales convolucionales
(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 ... -
Enhanced transfer learning model by image shifting on a square lattice for skin lesion malignancy assessment
Molina-Cabello, Miguel Ángel; Thurnhofer Hemsi, Karl; Maza Quiroga, Rosa María; Domínguez, Enrique; López-Rubio, Ezequiel; Molina-Cabello, Miguel Ángel[et al.] (2021)
Skin cancer is one of the most prevalent diseases among people. Physicians have a challenge every time they have to determine whether a diseased skin is benign or malign. There exist clinical diagnosis methods (such as ... -
Ensemble ellipse fitting by spatial median consensus
Thurnhofer Hemsi, Karl; López-Rubio, Ezequiel; Blázquez-Parra, Elidia Beatriz; Ladrón-de-Guevara-Muñoz, María del Carmen; De-Cózar-Macías, Óscar (2021)
Ellipses are among the most frequently used geometric models in visual pattern recognition and digital image analysis. This work aims to combine the outputs of an ensemble of ellipse fitting methods, so that the deleterious ... -
Histopathological image analysis for breast cancer diagnosis by ensembles of convolutional neural networks and genetic algorithms
Molina-Cabello, Miguel Ángel; Rodríguez Rodríguez, José Antonio; Thurnhofer Hemsi, Karl; López-Rubio, Ezequiel (2021-07)
One of the most invasive cancer types which affect women is breast cancer. Unfortunately, it exhibits a high mortality rate. Automated histopathological image analysis can help to diagnose the disease. Therefore, computer ... -
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 ... -
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, ...