• A reappraisal of echolalia in aphasia: A case-series study with multimodal neuroimaging 

      López-Barroso, Diana; Torres-Prioris, María José; Roé-Vellvé, Nuria; Thurnhofer-Hemsi, Karl; Paredes-Pacheco, José; [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 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; [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 ...
    • 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 ...
    • 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 A. (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 

      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 ...
    • Encoding generative adversarial networks for defense against image classification attacks 

      Rodríguez Rodríguez, José Antonio; Pérez Bravo, José María; García González, Jorge; Molina-Cabello, Miguel A.; Thurnhofer-Hemsi, Karl; [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 ...
    • Longitudinal study of the learning styles evolution in Engineering degrees 

      Molina-Cabello, Miguel A.; Thurnhofer-Hemsi, Karl; Domínguez, Enrique; López-Rubio, Ezequiel; Palomo, Esteban J. (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 A.; 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 A.; 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 ...
    • Panoramic Background Modeling for PTZ Cameras with Competitive Learning Neural Networks 

      Thurnhofer-Hemsi, Karl; López-Rubio, Ezequiel; Domínguez, Enrique; Luque-Baena, Rafael Marcos; Molina-Cabello, Miguel A. (2017-05-29)
      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 ...
    • Peer assessments in Engineering: A pilot project 

      Thurnhofer-Hemsi, Karl; Molina-Cabello, Miguel A.; Palomo, Esteban J.; López-Rubio, Ezequiel; Domínguez, Enrique (2021)
      The evaluation methods employed in a course are the most important point for the students, above any other learning aspect. For teachers, this task is arduous when the number of students is high. Traditional evaluation ...
    • Road pollution estimation using static cameras and neural networks 

      Molina-Cabello, Miguel A.; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel; Deka, lipika; Thurnhofer-Hemsi, Karl (2018-07-19)
      Este artículo presenta una metodología para estimar la contaminación en carreteras mediante el análisis de secuencias de video de tráfico. El objetivo es aprovechar la gran red de cámaras IP existente en el sistema de ...
    • Super- resolution of 3D MRI corrupted by heavy noise with the median filter transform 

      Thurnhofer-Hemsi, Karl; López-Rubio, Ezequiel; Roé Vellvé, Núria; Deka, lipika (2020-11-13)
      The acquisition of 3D MRIs is adversely affected by many degrading factors including low spatial resolution and noise. Image enhancement techniques are commonplace, but there are few proposals that address the increase of ...
    • Vehicle Type Detection by Convolutional Neural Networks 

      Molina-Cabello, Miguel A.; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel; Thurnhofer-Hemsi, Karl (Springer, 2017)
      In this work a new vehicle type detection procedure for traffic surveillance videos is proposed. A Convolutional Neural Network is integrated into a vehicle tracking system in order to accomplish this task. Solutions for ...