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108 results on '"Palomo, Esteban J."'

1. Coronary Artery Disease Classification with Different Lesion Degree Ranges based on Deep Learning

Author

Jiménez-Partinen, Ariadna, Thurnhofer-Hemsi, Karl, Palomo, Esteban J., Rodríguez-Capitán, Jorge, and Molina-Ramos, Ana I.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Invasive Coronary Angiography (ICA) images are considered the gold standard for assessing the state of the coronary arteries. Deep learning classification methods are widely used and well-developed in different areas where medical imaging evaluation has an essential impact due to the development of computer-aided diagnosis systems that can support physicians in their clinical procedures. In this paper, a new performance analysis of deep learning methods for binary ICA classification with different lesion degrees is reported. To reach this goal, an annotated dataset of ICA images that contains the ground truth, the location of lesions and seven possible severity degrees ranging between 0% and 100% was employed. The ICA images were divided into 'lesion' or 'non-lesion' patches. We aim to study how binary classification performance is affected by the different lesion degrees considered in the positive class. Therefore, five known convolutional neural network architectures were trained with different input images where different lesion degree ranges were gradually incorporated until considering the seven lesion degrees. Besides, four types of experiments with and without data augmentation were designed, whose F-measure and Area Under Curve (AUC) were computed. Reported results achieved an F-measure and AUC of 92.7% and 98.1%, respectively. However, lesion classification is highly affected by the degree of the lesion intended to classify, with 15% less accuracy when <99% lesion patches are present.

Published
2024
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2. CADICA: a new dataset for coronary artery disease detection by using invasive coronary angiography

Author

Jiménez-Partinen, Ariadna, Molina-Cabello, Miguel A., Thurnhofer-Hemsi, Karl, Palomo, Esteban J., Rodríguez-Capitán, Jorge, Molina-Ramos, Ana I., and Jiménez-Navarro, Manuel

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

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 evaluation based on ICA has several limitations, such as visual assessment of stenosis severity, which has significant interobserver variability. This motivates to development of a lesion classification system that can support specialists in their clinical procedures. Although deep learning classification methods are well-developed in other areas of medical imaging, ICA image classification is still at an early stage. One of the most important reasons is the lack of available and high-quality open-access datasets. In this paper, we reported a new annotated ICA images dataset, CADICA, to provide the research community with a comprehensive and rigorous dataset of coronary angiography consisting of a set of acquired patient videos and associated disease-related metadata. This dataset can be used by clinicians to train their skills in angiographic assessment of CAD severity and by computer scientists to create computer-aided diagnostic systems to help in such assessment. In addition, baseline classification methods are proposed and analyzed, validating the functionality of CADICA and giving the scientific community a starting point to improve CAD detection.

Published
2024
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3. Deep Learning-Based Classification of Invasive Coronary Angiographies with Different Patch-Generation Techniques

Author

Jiménez-Partinen, Ariadna, Palomo, Esteban J., Thurnhofer-Hemsi, Karl, Rodríguez-Capitán, Jorge, Molina-Ramos, Ana I., Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Ferrández Vicente, José Manuel, editor, Val Calvo, Mikel, editor, and Adeli, Hojjat, editor

Published
2024
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4. Parallel Processing Applied to Object Detection with a Jetson TX2 Embedded System

Author

Benito-Picazo, Jesús, Fernández-Rodríguez, Jose David, Domínguez, Enrique, Palomo, Esteban J., López-Rubio, Ezequiel, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, García Bringas, Pablo, editor, Pérez García, Hilde, editor, Martínez de Pisón, Francisco Javier, editor, Martínez Álvarez, Francisco, editor, Troncoso Lora, Alicia, editor, Herrero, Álvaro, editor, Calvo Rolle, José Luis, editor, Quintián, Héctor, editor, and Corchado, Emilio, editor

Published
2023
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7. A Novel Continual Learning Approach for Competitive Neural Networks

Author

Palomo, Esteban J., Ortiz-de-Lazcano-Lobato, Juan Miguel, Fernández-Rodríguez, José David, López-Rubio, Ezequiel, Maza-Quiroga, Rosa María, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ferrández Vicente, José Manuel, editor, Álvarez-Sánchez, José Ramón, editor, de la Paz López, Félix, editor, and Adeli, Hojjat, editor

Published
2022
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8. Peer Assessments in Engineering: A Pilot Project

Author

Thurnhofer-Hemsi, Karl, Molina-Cabello, Miguel A., Palomo, Esteban J., López-Rubio, Ezequiel, Domínguez, Enrique, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Gude Prego, Juan José, editor, de la Puerta, José Gaviria, editor, García Bringas, Pablo, editor, Quintián, Héctor, editor, and Corchado, Emilio, editor

Published
2022
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9. Longitudinal Study of the Learning Styles Evolution in Engineering Degrees

Author

Molina-Cabello, Miguel A., Thurnhofer-Hemsi, Karl, Domínguez, Enrique, López-Rubio, Ezequiel, Palomo, Esteban J., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Gude Prego, Juan José, editor, de la Puerta, José Gaviria, editor, García Bringas, Pablo, editor, Quintián, Héctor, editor, and Corchado, Emilio, editor

Published
2022
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10. Hierarchical Color Quantization with a Neural Gas Model Based on Bregman Divergences

Author

Palomo, Esteban J., Benito-Picazo, Jesús, Domínguez, Enrique, López-Rubio, Ezequiel, Ortega-Zamorano, Francisco, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Sanjurjo González, Hugo, editor, Pastor López, Iker, editor, García Bringas, Pablo, editor, Quintián, Héctor, editor, and Corchado, Emilio, editor

Published
2022
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15. Deep Learning-Based Security System Powered by Low Cost Hardware and Panoramic Cameras

Author

Benito-Picazo, Jesus, Domínguez, Enrique, Palomo, Esteban J., López-Rubio, Ezequiel, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Ferrández Vicente, José Manuel, editor, Álvarez-Sánchez, José Ramón, editor, de la Paz López, Félix, editor, Toledo Moreo, Javier, editor, and Adeli, Hojjat, editor

Published
2019
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18. Pixel Features for Self-organizing Map Based Detection of Foreground Objects in Dynamic Environments

Author

Molina-Cabello, Miguel A., López-Rubio, Ezequiel, Luque-Baena, Rafael Marcos, Domínguez, Enrique, Palomo, Esteban J., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Graña, Manuel, editor, López-Guede, José Manuel, editor, Etxaniz, Oier, editor, Herrero, Álvaro, editor, Quintián, Héctor, editor, and Corchado, Emilio, editor

Published
2017
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19. Motion Detection by Microcontroller for Panning Cameras

Author

Benito-Picazo, Jesús, López-Rubio, Ezequiel, Ortiz-de-Lazcano-Lobato, Juan Miguel, Domínguez, Enrique, Palomo, Esteban J., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Ferrández Vicente, José Manuel, editor, Álvarez-Sánchez, José Ramón, editor, de la Paz López, Félix, editor, Toledo Moreo, Javier, editor, and Adeli, Hojjat, editor

Published
2017
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21. Frame Size Reduction for Foreground Detection in Video Sequences

Author

Molina-Cabello, Miguel A., López-Rubio, Ezequiel, Luque-Baena, Rafael Marcos, Palomo, Esteban J., Domínguez, Enrique, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Luaces, Oscar, editor, Gámez, José A., editor, Barrenechea, Edurne, editor, Troncoso, Alicia, editor, Galar, Mikel, editor, Quintián, Héctor, editor, and Corchado, Emilio, editor

Published
2016
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31. A Self-Organized Multiagent System for Intrusion Detection

Author

Palomo, Esteban J., Domínguez, Enrique, Luque, Rafael M., Muñoz, Jose, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Cao, Longbing, editor, Gorodetsky, Vladimir, editor, Liu, Jiming, editor, Weiss, Gerhard, editor, and Yu, Philip S., editor

Published
2009
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32. A Neural Recognition System for Manufactured Objects

Author

Luque, Rafael M., Dominguez, Enrique, Palomo, Esteban J., Muñoz, Jose, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Omatu, Sigeru, editor, Rocha, Miguel P., editor, Bravo, José, editor, Fernández, Florentino, editor, Corchado, Emilio, editor, Bustillo, Andrés, editor, and Corchado, Juan M., editor

Published
2009
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33. A New GHSOM Model Applied to Network Security

Author

Palomo, Esteban J., Domínguez, Enrique, Luque, Rafael Marcos, Muñoz, José, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Kůrková, Véra, editor, Neruda, Roman, editor, and Koutník, Jan, editor

Published
2008
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34. A Neighborhood-Based Competitive Network for Video Segmentation and Object Detection

Author

Luque Baena, Rafael Marcos, Dominguez, Enrique, López-Rodríguez, Domingo, Palomo, Esteban J., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Kůrková, Véra, editor, Neruda, Roman, editor, and Koutník, Jan, editor

Published
2008
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38. Are learning styles useful? A new software to analyze correlations with grades and a case study in engineering.

Author

Molina‐Cabello, Miguel A., Thurnhofer‐Hemsi, Karl, Molina‐Cabello, David, and Palomo, Esteban J.

Subjects
COGNITIVE styles, ACADEMIC degrees, TEACHING guides, SCHOOL year, COMPUTER science
Abstract

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 is usually set in teaching guides according to the previous academic year's information without any knowledge of our current audience. In this work, a new software for learning styles and grade analysis based on the Honey‐Alonso Learning Styles Questionnaire has been proposed. This tool proposes the average learning style profiles of a given course by clustering student learning styles and analyzes the possible relation between grades and learning style profiles. By using that program, three different courses from Computer Sciences Engineering degrees during an academic year have been analyzed. The obtained results in our specific context exhibit that possible relation. This information could be useful to understand how students approach learning materials. [ABSTRACT FROM AUTHOR]

Published
2023
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41. Stenosis detection in coronary angiography images using deep learning models

Author

Luque-Baena, Rafael M., Romero Granados, Irene, Jiménez-Partinen, Ariadna, and Palomo, Esteban J.

Subjects
Aprendizaje automático (Inteligencia artificial), Convolutional neural networks, Procesado de imágenes, Coronary angiography images, Inteligencia artificial, Stenosis detection
Abstract

The emergence of deep learning has caused its massive application to different fields in industry and research, among which is the clinical field, especially in those where the data is structured in the form of images or video. The present proposal intends to develop a coronary angiography image analysis system based on artificial intelligence. These images are radiocontrast X-ray images of the coronary arteries. The proposed system will be able to analyze these coronary angiography images of patients with no obstructive coronary lesions to detect and characterize smooth and irregular coronary arteries and predict the presence of cardiovascular events during follow-up. Deep learning convolutional artificial neural networks will support the algorithmic basis of the proposed system. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.

Published
2022

42. Peer Assessments in Engineering: A Pilot Project

Author

Thurnhofer-Hemsi, Karl, Molina-Cabello, Miguel A., Palomo, Esteban J., López-Rubio, Ezequiel, and Domínguez, Enrique

Subjects
Enseñanza superior - Congresos, higher education, cooperative assessment, ComputingMilieux_COMPUTERSANDEDUCATION, Ingeniería - Estudio y enseñanza - Congresos, Peer assessment, web-based education
Abstract

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 requires the teacher to grade all the assignments and exams, while peer assessments have become a valuable tool to involve students effectively in the correction of exercises. This paper applied and analyzes the evaluation through peer review in a course of Computer Sciences Engineering. A total of six assignments and a mid-term exam were evaluated by both teachers (individually) and students (cooperatively), and the differences were discussed to extract conclusions about the viability of this evaluation model. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.

Published
2021

43. Longitudinal Study of the Learning Styles Evolution in Engineering Degrees

Author

Molina-Cabello, Miguel A., Thurnhofer-Hemsi, Karl, Domínguez, Enrique, López-Rubio, Ezequiel, and Palomo, Esteban J.

Subjects
Learning styles, Enseñanza superior - Congresos, higher education, grades, Ingeniería - Estudio y enseñanza, web-based education
Abstract

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 and evaluation. By using the Honey-Alonso Learning Styles Questionnaire (CHAEA), in this work, we carried out a longitudinal study of the correlation between marks and the results of the survey. The 2018/2019, 2019/2020, and 2020/2021 academic years in two different courses from Computer Sciences engineering degrees were studied. The results were analyzed in order to evaluate the impact of the adaptation to digital lessons during the last year. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.

Published
2021

47. Hierarchical Color Quantization with a Neural Gas Model Based on Bregman Divergences

Author

Palomo, Esteban J., Benito Picazo, Jesús, Domínguez-Merino, Enrique, López-Rubio, Ezequiel, and Ortega-Zamorano, Francisco

Subjects
Self-organization, Redes neuronales artificiales, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Color quantization, Clustering, Neural networks
Abstract

In this paper, a new color quantization method based on a self-organized artificial neural network called the Growing Hierarchical Bregman Neural Gas (GHBNG) is proposed. This neural network is based on Bregman divergences, from which the squared Euclidean distance is a particular case. Thus, the best suitable Bregman divergence for color quantization can be selected according to the input data. Moreover, the GHBNG yields a tree-structured model that represents the input data so that a hierarchical color quantization can be obtained, where each layer of the hierarchy contains a different color quantization of the original image. Experimental results confirm the color quantization capabilities of this approach. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.

Published
2021

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