Journals

  • A. Jiménez-Partinen, M.A. Molina-Cabello, K. Thurnhofer-Hemsi, E.J. Palomo, J. Rodríguez-Capitán, A.I. Molina-Ramos, M. Jiménez-Navarro, CADICA: A new dataset for coronary artery disease detection by using invasive coronary angiography, Expert Systems, vol. 41, no. 12, pp. 1-17, 2024. (DOI: 10.1111/exsy.13708).

  • A. Jiménez-Partinen, K. Thurnhofer-Hemsi, J. Rodríguez-Capitán, A.I. Molina-Ramos, E.J. Palomo, Coronary Artery Disease Classification With Different Lesion Degree Ranges Based on Deep Learning, IEEE Access, vol. 12, pp. 69229-69239, 2024. (DOI: 10.1109/ACCESS.2024.3401465).

  • J.D. Fernández-Rodríguez, E.J. Palomo, J. Benito-Picazo, E. Domínguez, E. López-Rubio and F. Ortega-Zamorano, A Convolutional Autoencoder and a Neural Gas Model based on Bregman Divergences for Hierarchical Color Quantization, Neurocomputing, vol. 544, 126288, 2023. (DOI: 10.1016/j.neucom.2023.126288).

  • J.D. Fernández-Rodríguez, E.J. Palomo, J.M. Ortiz-de-Lazcano-Lobato, G. Ramos-Jiménez and E. López-Rubio, Dynamic Learning Rates for Continual Unsupervised Learning, Integrated Computer-Aided Engineering, vol. 30, no. 3, pp. 257-273, 2023. (DOI: 10.3233/ICA-230701).

  • M.A. Molina-Cabello, K. Thurnhofer-Hemsi, D. Molina-Cabello and E.J. Palomo, Are learning styles useful? A new software to analyze correlations with grades and a case study in engineering, Computer Applications in Engineering Education, vol. 31, no. 3, pp. 537-551, 2022. (DOI: 10.1002/cae.22597).

  • E.J. Palomo, E. López-Rubio, F. Ortega-Zamorano and R. Benítez-Rochel, Exploratory Data Analysis and Foreground Detection with the Growing Hierarchical Neural Forest, Neural Processing Letters, vol. 52, no. 3, pp. 2537-2563, 2020. (DOI: 10.1007/s11063-020-10360-2).

  • J. Benítez-Picazo, E. Domínguez, E.J. Palomo and E. López-Rubio, Deep learning-based video surveillance system managed by low cost hardware and panoramic cameras, Integrated Computer-Aided Engineering, vol. 27, no. 4, pp. 373-387, 2020. (DOI: 10.3233/ICA-200632).

  • A. Díaz-Ramos, E.J. Palomo and E. López-Rubio, The Forbidden Region Self-Organizing Map neural network, IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 1, pp. 201-211, 2019. (DOI: 10.1109/TNNLS.2019.2900091).

  • A. Muñoz, E.J. Palomo and A. Jerez-Calero, Use of an ANN to Value MTF and Melatonin Effect on ADHD Affected Children, IEEE Access, vol. 7, pp. 127254-127264, 2019. (DOI: 10.1109/ACCESS.2019.2937573).

  • J. Benítez-Picazo, E. Domínguez, E.J. Palomo, E. López-Rubio and J.M. Ortiz-de-Lazcano-Lobato, Motion detection with low cost hardware for PTZ cameras, Integrated Computer-Aided Engineering, vol. 26, no. 1, pp. 21-36, 2019. (DOI: 10.3233/ICA-180579).

  • M.A. Molina-Cabello, E. López-Rubio, R.M. Luque-Baena, E. Domínguez and E.J. Palomo, Foreground object detection for video surveillance by fuzzy logic based estimation of pixel illumination states, Logic Journal of the IGPL, 2018. (DOI: 10.1093/jigpal/jzy024).

  • A. Díaz-Ramos, E. López-Rubio and E.J. Palomo, The Role of the Lattice Dimensionality in the Self-Organizing Map, Neural Network World, vol. 1, no. 28, 2018. (DOI: 10.14311/NNW.2018.28.004).

  • E. López-Rubio, E.J. Palomo and F. Ortega-Zamorano, Unsupervised Learning by Cluster Quality Optimization, Information Sciences, 2018. (DOI: 10.1016/j.ins.2018.01.007).

  • E. López-Rubio, R.M. Luque-Baena, E.J. Palomo and E. Domínguez, Dynamic Tree Topology Learning by Self-Organization, Neural Computing and Applications, vol. 28, no. 5, pp. 911-924, 2017. (DOI: 10.1007/s00521-016-2250-7).

  • E. López-Rubio, J.F. López-Rubio, M.A. Molina-Cabello, R.M. Luque-Baena, E.J. Palomo and E. Domínguez, The Effect of Noise on Foreground Detection Algorithms, Artificial Intelligence Review, pp. 1-32, 2016. (DOI: 10.1007/s10462-016-9525-3).

  • J.G. Monroy, E.J. Palomo, E. López-Rubio and J. González-Jiménez, Continuous Chemical Classification in Uncontrolled Environments with Sliding Windows, Chemometrics and Intelligent Laboratory Systems, vol. 158, pp. 117-129, 2016.

  • F. Ortega-Zamorano, M.A. Molina-Cabello, E. López-Rubio and E.J. Palomo, Smart motion detection sensor based on video processing using self-organizing maps, Expert Systems with Applications, vol. 64, pp. 476-489, 2016. (DOI: 10.1016/j.eswa.2016.08.010).

  • E.J. Palomo and E. López-Rubio, The Growing Hierarchical Neural Gas Self-Organizing Neural Network, IEEE Transactions on Neural Networks and Learning Systems, no. 99, pp. 1-10, 2016. (DOI: 10.1109/TNNLS.2016.2570124).

  • E.J. Palomo and E. López-Rubio, Learning Topologies with the Growing Neural Forest, International Journal of Neural Systems, vol. 26, no. 4, pp. 1650019 (21 pages), 2016. (DOI: 10.1142/S0129065716500192).

  • F.J. López-Rubio, E. Domínguez, E.J. Palomo, E. López-Rubio and R.M. Luque-Baena, Selecting the Color Space for Self-Organizing Map Based Foreground Detection in Video, Neural Processing Letters, vol. 43, no. 2, pp. 345-361, 2016. (DOI: 10.1007/s11063-015-9431-8).

  • R.M. Luque-Baena, E. López-Rubio, E. Domínguez, E.J. Palomo, J.M. Jerez, A Self-Organizing Map to Improve Vehicle Detection in Flow Monitoring Systems, Soft Computing, vol. 19, no. 9, pp. 2499-2509, 2015. (DOI: 10.1007/s00500-014-1575-3).

  • E. López-Rubio, E.J. Palomo and E. Domínguez, Robust Self-Organization with M-Estimators, Neurocomputing, vol. 151, Part 1, pp. 408-423, 2015.

  • E.J. Palomo, E. López-Rubio and E. Domínguez, Bregman Divergences for Growing Hierarchical Self-Organizing Networks, International Journal of Neural Systems, vol. 24, no. 4, pp. 1-18, 2014.

  • E.J. Palomo and E. Domínguez, Hierarchical Color Quantization based on Self-Organization, Journal of Mathematical Imaging and Vision, vol. 49, no. 1, pp. 1-19, 2014.

  • E.J. Palomo, D. Elizondo and G. Brunschwig, Land Usage Classification: A Hierarchical Neural Network Approach, Journal of Agricultural Science, Cambridge University Press, vol. 152, no. 5, pp. 817-828, 2014.

  • R.M. Luque, D. Elizondo, E. López-Rubio, E.J. Palomo and T. Watson, Assessment of Geometric Features for Individual Identification and Verification in Biometric Hand Systems, Expert Systems with Applications, vol. 40, pp. 3580-3594, 2013.

  • R.M. Luque, J.M. Ortiz-de-Lazcano-Lobato, E. López-Rubio, E. Domínguez and E.J. Palomo, A Competitive Neural Network for Multiple Object Tracking in Video Sequence Analysis, Neural Processing Letters, vol. 37, pp. 47-67, 2013.

  • E.J. Palomo, E. Domínguez, R.M. Luque and J. Muñoz, Image Compression and Video Segmentation using Hierarchical Self-Organization, Neural Processing Letters, vol. 37, pp. 69-87, 2013.

  • E.J. Palomo, J. North, D. Elizondo, R.M. Luque and T. Watson, Application of growing hierarchical SOM for visualisation of network forensics traffic data, Neural Networks, vol. 32, pp. 275-284, 2012.

  • E. López-Rubio and, E.J. Palomo, Growing hierarchical probabilistic self-organizing graphs, IEEE Trans. on Neural Networks, vol. 22, no 7, pp. 997-1008, 2011.

  • E. López-Rubio, E.J. Palomo, J.M. Ortiz-de-Lazcano-Lobato and M.C. Vargas-González, Dynamic topology learning with the probabilistic self-organizing graph, Neurocomputing, vol. 74, pp. 2633- 2648, 2011.

  • E.J. Palomo, E. Dominguez, R.M. Luque and J. Muñoz, An Intrusion Detection System based on Hierarchical Self-Organization, Journal of Information Assurance and Security vol. 4, no. 3, pp. 209-216, 2009.

    • Conference Proceedings

  • Jesús Benito-Picazo, José David Fernández-Rodríguez, Enrique Domínguez, Esteban J. Palomo and Ezequiel López-Rubio, "Parallel Processing Applied to Object Detection with a Jetson TX2 Embedded System", 18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023), LNCS, vol. 750, 2023. (DOI: 10.1007/978-3-031-42536-3_18).

  • E.J. Palomo, M.A. Zafra-Santisteban and R.M Luque-Baena, “Pneumonia Detection in Chest X-ray Images using Convolutional Neural Networks”, 2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), pp. 16-21, 2022. (DOI: 10.1109/MetroXRAINE54828.2022.9967590).

  • R.M Luque-Baena, I.R. Granados, A. Jiménez-Partinen, E.J. Palomo, M. Jiménez-Navarro, “Stenosis Detection in Coronary Angiography Images using Deep Learning Models”, 2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), pp. 22-27, 2022. (DOI: 10.1109/MetroXRAINE54828.2022.9967696).

  • E.J. Palomo, Juan M. Ortiz-de-Lazcano-Lobato, José D. Fernández-Rodríguez, E. López-Rubio and Rosa M. Maza-Quiroga, “A Novel Continual Learning Approach for Competitive Neural Networks”, 9th International Work-Conference on the Interplay Between Natural and Artificial Computation (IWINAC 2022), Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence, LNCS, vol. 13259, pp. 223-232, 2022. (DOI: 10.1007/978-3-031-06527-9_22).

  • Hector Mejia, Esteban J. Palomo, Ezequiel Lopez-Rubio, Israel Pineda, Rigoberto Fonseca-Delgado, "Vehicle Speed Estimation Using Computer Vision and Evolutionary Camera Calibration", Neural Information Processing Systems Conference: LatinX in AI (LXAI), 2021. (DOI: 10.52591/lxai202112072)

  • Jesús Benito-Picazo, Enrique Domínguez, Esteban J. Palomo, Gonzalo Ramos-Jiménez and Ezequiel López-Rubio, "Deep learning-based anomalous object detection system for panoramic cameras managed by a Jetson TX2 board", 2021 International Joint Conference on Neural Networks (IJCNN), pp. 1-7, 2021. (DOI: 10.1109/IJCNN52387.2021.9534053).

  • Esteban J. Palomo, Jesús Benito-Picazo, Enrique Domínguez, Ezequiel López-Rubio and Francisco Ortega-Zamorano, "Hierarchical Color Quantization with a Neural Gas Model Based on Bregman Divergences", 16th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2021), Advances in Intelligent Systems and Computing, vol. 1401, pp. 327-337, 2021. (DOI: 10.1007/978-3-030-87869-6_31).

  • Karl Thurnhofer-Hemsi, Miguel A. Molina-Cabello, Esteban J. Palomo, Ezequiel López-Rubio, and Enrique Domínguez, "Peer Assessments in Engineering: A Pilot Project", 12th International Conference on EUropean Transnational Educational (ICEUTE 2021), Advances in Intelligent Systems and Computing, vol. 1400, pp. 274-283, 2021. (DOI: 10.1007/978-3-030-87872-6_27).

  • Miguel A. Molina-Cabello, Karl Thurnhofer-Hemsi, Enrique Domínguez, Ezequiel López-Rubio, and Esteban J. Palomo, "Longitudinal Study of the Learning Styles Evolution in Engineering Degrees", 12th International Conference on EUropean Transnational Educational (ICEUTE 2021), Advances in Intelligent Systems and Computing, vol. 1400, pp. 264-273, 2021. (DOI: 10.1007/978-3-030-87872-6_26).

  • Jesús Benito-Picazo, Antonio Díaz Ramos, Esteban J. Palomo and Enrique Domínguez, "Image Clustering using a Growing Neural Gas with Forbidden Regions", 2020 International Joint Conference on Neural Networks (IJCNN), 2020. (DOI: 10.1109/IJCNN48605.2020.9207700).

  • J. Benito-Picazo, E. Domínguez, E.J. Palomo and E. López-Rubio, “Deep Learning-Based Security System Powered by Low Cost Hardware and Panoramic Cameras”, From Bioinspired Systems and Biomedical Applications to Machine Learning (IWINAC), LNCS, vol. 11487, pp. 317-326, 2019. (DOI: 10.1007/978-3-030-19651-6_31).

  • Esteban J. Palomo, Miguel A. Molina-Cabello, Ezequiel López-Rubio and Rafael Marcos Luque Baena, "A New Self-Organizing Neural Gas Model based on Bregman Divergences", 2018 International Joint Conference on Neural Networks (IJCNN), pp. 1-8, 2018. (DOI: 10.1109/IJCNN.2018.8489545).

  • Jesús Benito-Picazo, Enrique Domínguez, Esteban J. Palomo, Ezequiel López-Rubio and Juan Miguel Ortiz-de-Lazcano-Lobato, "Deep learning-based anomalous object detection system powered by microcontroller for PTZ cameras", 2018 International Joint Conference on Neural Networks (IJCNN), pp. 1-7, 2018. (DOI: 10.1109/IJCNN.2018.8489437).

  • E.J. Palomo, J. Benito-Picazo, E. López-Rubio and E. Domínguez, “Unsupervised Color Quantization with the Growing Neural Forest”, Advances in Computational Intelligence, LNCS, vol. 10306, pp. 306-316, 2017. (DOI: 10.1007/978-3-319-59147-6_27).

  • J. Benito-Picazo, E. López-Rubio, J.M. Ortiz-de-Lazcano-Lobato, E. Domínguez and E.J. Palomo, “Motion Detection by Microcontroller for Panning Cameras”, Advances in Computational Intelligence, LNCS, vol. 10338, pp. 279-288, 2017. (DOI: 10.1007/978-3-319-59773-7_29).

  • M.A. Molina-Cabello, E. López-Rubio, R.M. Luque, E. Domínguez and E.J. Palomo, “Pixel Features for Self-organizing Map Based Detection of Foreground Objects in Dynamic Environments”, Advances in Intelligent Systems and Computing, vol. 527, pp. 247-255, 2016. (DOI: 10.1007/978-3-319-47364-2_24).

  • M.A. Molina-Cabello, E. López-Rubio, R.M. Luque, E.J. Palomo and E. Domínguez, “Frame Size Reduction for Foreground Detection in Video Sequences”, Advances in Artificial Intelligence, LNAI, vol. 9868, pp. 3-12, 2016. (DOI: 10.1007/978-3-319-44636-3_1).

  • E.J. Palomo and E. López-Rubio, "A Color Quantization Approach based on the Growing Neural Forest", 2016 IEEE Latin American Conference on Computational Intelligence (2016 IEEE LA-CCI), pp. 1-2, 2016. (DOI: 10.1109/LA-CCI.2016.7885744).

  • E. López-Rubio, E.J. Palomo, R.M. Luque and E. Domínguez, “Visualization of Complex Datasets with the Self-Organizing Spanning Tree”, Advances in Computational Intelligence, LNCS, vol. 9094, pp. 209-217, 2015. (DOI: 10.1007/978-3-319-19258-1_18).

  • Enrique Machuca Sánchez, Ana Belén Ruiz-Mora, Isabel Ruiz-Mora, Guianluigui Moscato, Gema Ruiz-Párraga, Mónica Carreira Soler, Sergio Postigo Pozo, Efraín Ochoa Martínez, Esteban Palomo Ferrer y Alberto García Moreno, "Los Planes Postdoctorales de Investigación en España: Análisis de Financiación Local para Jóvenes Doctores", XII Foro Internacional sobre la Evaluación de la Calidad de la Investigación y de la Educación Superior (FECIES), 2015.

  • R.M. Luque-Baena, E.J. Palomo, E. López-Rubio, E. Domínguez and F.J. López-Rubio, "Seleccion del espacio de color para video-segmentacion mediante redes neuronales autorganizadas", X Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB 2015), pp. 723-731, 2015.

  • F. J. Lopez-Rubio, E. Lopez-Rubio, R. M. Luque-Baena, E. Dominguez and E.J. Palomo, “Color Space Selection for Self-Organizing Map Based Foreground Detection in Video Sequences,”, International Joint Conference on Neural Networks (IJCNN), pp. 3347-3354, 2014. (DOI: 10.1109/IJCNN.2014.6889404).

  • E.J. Palomo, E. López-Rubio, E. Domínguez and R.M. Luque, “Hierarchical Self-Organizing Networks for Multispectral Data Visualization”, Advances in Computational Intelligence, LNCS, vol. 7903, pp. 449-457, 2013. (DOI: 10.1007/978-3-642-38682-4_48).

  • R.M. Luque, E. López-Rubio, E. Domínguez, E.J. Palomo and J.M. Jerez, “A Self-Organizing Map for Traffic Flow Monitoring”, Advances in Computational Intelligence, LNCS, vol. 7903, pp. 458-466, 2013. (DOI: 10.1007/978-3-642-38682-4_49).

  • E.J. Palomo, E. Domínguez, R.M. Luque, Muñoz J. “Lossy Image Compression Using a GHSOM”, Advances in Computational Intelligence, LNCS, vol 6692, pp. 1‐8, 2011. (DOI: 10.1007/978-3-642-21498-1_1).

  • R.M. Luque, Ortiz‐de‐Lazcano‐Lobato, J.M, López‐Rubio, E. E. Domínguez, E.J. Palomo, “Feature Weighting In Competitive Learning For Multiple Object Tracking In Video Sequences”, Advances in Computational Intelligence, LNCS, vol. 6692, pp. 17‐24, 2011. (DOI: 10.1007/978-3-642-21498-1_3).

  • Palomo, E.J. and Domínguez, E., "Image compression based on growing hierarchical self-organizing maps", International Joint Conference on Neural Networks (IJCNN), pp.1624-1628, 2011. (DOI: 10.1109/IJCNN.2011.6033419).

  • Luque, R.M.; Elizondo, D., Lopez-Rubio, E.; Palomo, E.J.; "GA-based feature selection approach in biometric hand systems", International Joint Conference on Neural Networks (IJCNN), pp.246-253, 2011. (DOI: 10.1109/IJCNN.2011.6033228).

  • Palomo, E.J.; North, J., Elizondo, D.; Luque, R.M.; Watson, T.; "Visualisation of network forensics traffic data with a self-organising map for qualitative features", International Joint Conference on Neural Networks (IJCNN), pp.1740-1747, 2011. (DOI: 10.1109/IJCNN.2011.6033434).

  • E.J. Palomo, J.M. Ortiz-de-Lazcano-Lobato, E. Domínguez and R.M. Luque, “An anomaly detection system using a GHSOM-1”, Intenational Joint Conference on Neural Networks (IJCNN), pp. 691-697, 2010. (DOI: 10.1109/IJCNN.2010.5596967).

  • R.M. Luque, E. Domínguez, E.J. Palomo and J. Muñoz, 2010. “An ART-type network approach for video object detection”, 18th European Symposium on Artificial Neural Networks, ESANN, pp. 423-428, 2010.

  • E.J. Palomo, E. Domínguez, R.M. Luque, Muñoz J., “Web Document Clustering based on a Hierarchical Self-Organizing Model”, 18th European Symposium on Artificial Neural Networks, ESANN, pp. 499-504, 2010.

  • R.M. Luque, J.M. Ortiz-de-Lazcano-Lobato, E. Lopez-Rubio and E.J. Palomo, "Object Tracking in Video Sequences by Unsupervised Learning", Computer Analysis of Images and Patterns, LNCS, vol. 5702, pp. 1070-1077, 2009. (DOI: 10.1007/978-3-642-03767-2_130).

  • R.M. Luque, E. Dominguez, E.J. Palomo and J. Muñoz, "A Neural Recognition System for Manufactured Objects", Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living, LNCS, vol. 5518, pp. 1274-1281, 2009. (DOI: 10.1007/978-3-642-02481-8_189).

  • E.J. Palomo, J.M. Ortiz-de-Lazcano-Lobato, D. Lopez-Rodriguez and R.M. Luque, "Hierarchical Graphs for Data Clustering", Bio-Inspired Systems: Computational and Ambient Intelligence, LNCS, Volume 5517, 2009, pp. 432-439, 2009. (DOI: 0.1007/978-3-642-02478-8_54).

  • E.J. Palomo, E. Dominguez, R.M. Luque, J. Muñoz, “Image Hierarchical Segmentation Based on a GHSOM”, International Conference on Neural Information Processing (ICONIP). LNCS Vol 5863; pp. 743-750, 2009. (DOI: 10.1007/978-3-642-10677-4_85).

  • E.J. Palomo, E. Dominguez, R.M. Luque and J. Muñoz, "Spam Detection Based on a Hierarchical Self-Organizing Map", Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence, LNCS, vol. 5755, pp. 30-37, 2009. (DOI: 10.1007/978-3-642-04020-7_4).

  • E.J. Palomo, E. Dominguez, R.M. Luque and J. Muñoz, "An Intrusion Detection System based on Hierarchical Self-Organization", International Workshop on Computational Intelligence in Security for Information Systems (CISIS), vol. 53, pp. 139-146, 2009. (DOI: 10.1007/978-3-540-88181-0_18).

  • E.J. Palomo, E. Dominguez, R.M. Luque and J. Muñoz, "Network Security Using Growing Hierarchical Self-Organizing Maps", Adaptive and Natural Computing Algorithms, LNCS, vol. 5495, pp. 130-139, 2009. (DOI: 10.1007/978-3-642-04921-7_14).

  • J.M. Ortiz-de-Lazcano-Lobato, R.M. Luque, D. Lopez-Rodriguez and E.J. Palomo, "Growing Competitive Network for Tracking Objects in Video Sequences", Adaptive and Natural Computing Algorithms, LNCS, vol. 5495, pp. 109-118, 2009. (DOI: 10.1007/978-3-642-04921-7_12).

  • E.J. Palomo, E. Domínguez, R.M. Luque and J. Muñoz, "A Self-Organized Multiagent System for Intrusion Detection", Agents and Data Mining Interaction, LNCS, vol. 5680, pp. 84-94, 2009. (DOI: 10.1007/978-3-642-03603-3_7).

  • R.M. Luque, E. Dominguez, J. Muñoz and E.J. Palomo "Un modelo neuronal de agrupamiento basado en regiones para segmentación de vídeo", XIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA) pp. 243-252, 2009.

  • E.J. Palomo, E. Dominguez, R.M. Luque and J. Muñoz, "A New GHSOM Model Applied to Network Security", Artificial Neural Networks - ICANN 2008, LNCS, vol. 5163, pp. 680-689, 2008. (DOI: 10.1007/978-3-540-87536-9_70).

  • R.M. Luque, E. Dominguez, D. Lopez-Rodriguez and E.J. Palomo, "A Neighborhood-Based Competitive Network for Video Segmentation and Object Detection", Artificial Neural Networks - ICANN 2008, LNCS, Volume 5163, pp. 877-886, 2008. (DOI: 10.1007/978-3-540-87536-9_90).

  • E.J. Palomo, E. Dominguez, R.M. Luque and J. Muñoz, "A Competitive Neural Network for Intrusion Detection Systems", Modelling, Computation and Optimization in Information Systems and Management Sciences (MCO) vol. 14, pp. 530-537, 2008. (DOI: 10.1007/978-3-540-87477-5_56).

  • R.M. Luque, E. Domínguez, E.J. Palomo and J. Muñoz, "A Neural Network Approach for Video Object Segmentation in Traffic Surveillance", Image Analysis and Recognition, LNCS, vol. 5112, pp. 151-158, 2008. (DOI: 10.1007/978-3-540-69812-8_15).

  • R.M. Luque, D. Lopez-Rodriguez, E. Domínguez and E.J. Palomo, "A Dipolar Competitive Neural Network for Video Segmentation", Advances in Artificial Intelligence – IBERAMIA, LNCS, Volume 5290, pp. 103-112, 2008. (DOI: 10.1007/978-3-540-88309-8_11).

  • R.M. Luque, F.L. Valverde, E. Dominguez, E.J. Palomo and J. Muñoz "Detecting Critical Situation in Public Transport", International Workshop on Pattern Recognition in Information Systems (PRIS) pp. 57-66, 2008. (DOI: 10.1007/978-3-540-88309-8_11).

  • R.M. Luque, D. Lopez-Rodriguez, E. Mérida-Casermeiro and E.J. Palomo "Video Object Segmentation with Multivalued Neural Networks", Eighth International Conference on Hybrid Intelligent Systems, HIS '08 pp. 613-618, 2008. (DOI: 10.1109/HIS.2008.130).

  • J.M. Ortiz-de-Lazcano-Lobato, R.M. Luque, D. Lopez-Rodriguez and E.J. Palomo "A Novel Competitive Network Approach to Object Tracking", Proceedings of the UK Workshop on Computational Intelligence pp. 111-116, 2008.

  • E. Dominguez, C. Spinola, R.M. Luque, E.J. Palomo and J. Muñoz "Object recognition and inspection in difficult industrial environments", IEEE International Conference on Industrial Technology (ICIT) pp. 989-993, 2006.

    • Chapter Books

  • E.J. Palomo, D. Elizondo, E. Domínguez, R.M. Luque, and Tim Watson, “SOM‐based Techniques towards Hierarchical Visualisation of Network Forensics Traffic Data”, Computational Intelligence for Privacy and Security, Springer, vol. 394, pp. 75-95, 2012. (DOI: 10.1007/978-3-642-25237-2_6).

  • R. M. Luque, D. Elizondo, E. López‐Rubio, and E.J. Palomo, “Feature Selection of Hand Biometrical Traits based on Computational Intelligence Techniques”, Computational Intelligence for Privacy and Security, Springer, vol. 394, pp. 159-180, 2012. (DOI: 10.1007/978-3-642-25237-2_10).



    • Sites of Interest

    CONTACT

    Phone: +34-952-132726
    Fax: +34-952-131397
    Email: ejpalomo@lcc.uma.es
    University of Malaga
    Department of Computer Science
    Bulevar Louis Pasteur, 35
    Campus de Teatinos
    29071 Málaga (Spain)