David A. Elizondo

发表

SOM-Based Techniques towards Hierarchical Visualisation of Network Forensics Traffic Data

Esteban J. Palomo, David A. Elizondo, Enrique Domínguez, 2012, Computational Intelligence for Privacy and Security.

A Constructive Neural Network for Evolving a Machine Controller in Real-Time

David A. Elizondo, Andreas Huemer, Mario A. Góngora, 2009, Constructive Neural Networks.

Intelligence Techniques in Computer Security and Forensics: At the Boundaries of Ethics and Law

Yingqin Zheng, Bernd Carsten Stahl, David A. Elizondo, 2012, Computational Intelligence for Privacy and Security.

Surface Reconstruction Techniques Using Neural Networks to Recover Noisy 3D Scenes

David A. Elizondo, Charalambos Chrysostomou, Shang-Ming Zhou, 2008, ICANN.

Application of Fuzzy Logic in Computer Security and Forensics

Sulaiman Al Amro, David A. Elizondo, Francisco Chiclana, 2012, Computational Intelligence for Privacy and Security.

Visualisation of network forensics traffic data with a self-organising map for qualitative features

Esteban J. Palomo, David A. Elizondo, Rafael Marcos Luque Baena, 2011, The 2011 International Joint Conference on Neural Networks.

GA-based feature selection approach in biometric hand systems

Ezequiel López-Rubio, Esteban J. Palomo, David A. Elizondo, 2011, The 2011 International Joint Conference on Neural Networks.

Constructive Recursive Deterministic Perceptron Neural Networks with Genetic Algorithms

David A. Elizondo, Tim Watson, Benjamin N. Passow, 2013, Int. J. Pattern Recognit. Artif. Intell..

The linear separability problem: some testing methods

David A. Elizondo, D. Elizondo, 2006, IEEE Transactions on Neural Networks.

Ethical and legal issues of the use of computational intelligence techniques in computer security and computer forensics

Yingqin Zheng, Bernd Carsten Stahl, David A. Elizondo, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Analysis and test of efficient methods for building recursive deterministic perceptron neural networks

Éric D. Taillard, David A. Elizondo, Mario A. Góngora, 2007, Neural Networks.

Foreground detection by ensembles of random polygonal tilings

Miguel A. Molina-Cabello, Ezequiel López-Rubio, David A. Elizondo, 2020, Expert Syst. Appl..

A robust reinforcement based self constructing neural network

David A. Elizondo, Andreas Huemer, Mario A. Góngora, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Choice effect of linear separability testing methods on constructive neural network algorithms: An empirical study

Juan Miguel Ortiz-de-Lazcano-Lobato, David A. Elizondo, Ralph Birkenhead, 2011, Expert Syst. Appl..

Computational Intelligence Techniques in Medicine

Ezequiel López-Rubio, David A. Elizondo, Rafael Marcos Luque Baena, 2015, Comput. Math. Methods Medicine.

Linear separability and classification complexity

David A. Elizondo, Matías Gámez, Ralph Birkenhead, 2012, Expert Syst. Appl..

Assessment of geometric features for individual identification and verification in biometric hand systems

Ezequiel López-Rubio, Esteban J. Palomo, David A. Elizondo, 2013, Expert Syst. Appl..

Adapting traffic simulation for traffic management: A neural network approach

David A. Elizondo, Francisco Chiclana, Eric Goodyer, 2013, 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013).

Constructive Neural Network Algorithms for Feedforward Architectures Suitable for Classification Tasks

Maria do Carmo Nicoletti, David A. Elizondo, Leonardo Franco, 2009, Constructive Neural Networks.

A Reward-Value Based Constructive Method for the Autonomous Creation of Machine Controllers

David A. Elizondo, Andreas Huemer, Mario A. Góngora, 2008, ICANN.

A Novel Method for Extracting Knowledge from Neural Networks with Evolving SQL Queries

David A. Elizondo, Tim Watson, Mario A. Góngora, 2005, ICANN.

Non-ontogenic sparse neural networks

David A. Elizondo, Emile Fiesler, Jerzy J. Korczak, 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

A Novel and Efficient Method for Testing Non Linear Separability

Juan Miguel Ortiz-de-Lazcano-Lobato, David A. Elizondo, Ralph Birkenhead, 2007, ICANN.

Multiple sensor outputs and computational intelligence towards estimating state and speed for control of lower limb prostheses

David A. Elizondo, Benjamin N. Passow, Pamela A. Hardaker, 2014, 2014 14th UK Workshop on Computational Intelligence (UKCI).

The Generalisation of the Recursive Deterministic Perceptron

Éric D. Taillard, David A. Elizondo, Ralph Birkenhead, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

New methods for testing linear separability

David A. Elizondo, Mohamed Tajine, D. Elizondo, 2002, Neurocomputing.

State detection from electromyographic signals towards the control of prosthetic limbs

David A. Elizondo, Benjamin N. Passow, Pamela A. Hardaker, 2013, 2013 13th UK Workshop on Computational Intelligence (UKCI).

Growing Methods for Constructing Recursive Deterministic Perceptron Neural Networks and Knowledge Extraction

David A. Elizondo, Mohamed Tajine, 1998, Artif. Intell..

Aggregation of Convolutional Neural Network Estimations of Homographies by Color Transformations of the Inputs

Miguel A. Molina-Cabello, Ezequiel López-Rubio, David A. Elizondo, 2020, IEEE Access.

Pose invariance through registration for hierarchical feature based pattern recognition systems

David A. Elizondo, Benjamin N. Passow, Noel Khan, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Current Trends on Knowledge Extraction and Neural Networks

David A. Elizondo, Mario A. Góngora, D. Elizondo, 2005, ICANN.

Editorial A Successful Change From TNN to TNNLS and a Very Successful Year

Igor Skrjanc, Giorgio Battistelli, Thomas Villmann, 2013, IEEE Trans. Neural Networks Learn. Syst..

Evolving a neural network using dyadic connections

David A. Elizondo, Andreas Huemer, Mario A. Góngora, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Computational Intelligence for Privacy and Security: Introduction

Agusti Solanas, David A. Elizondo, Antoni Martínez-Ballesté, 2012, Computational Intelligence for Privacy and Security.

Self Constructing Neural Network Robot Controller based on On-line Task Performance Feedback

David A. Elizondo, Andreas Huemer, Mario A. Góngora, 2008, ICINCO-ICSO.

Bankruptcy forecasting: An empirical comparison of AdaBoost and neural networks

David A. Elizondo, Matías Gámez, Esteban Alfaro Cortés, 2008, Decis. Support Syst..

On the Generalization of the m-Class RDP Neural Network

Juan Miguel Ortiz-de-Lazcano-Lobato, David A. Elizondo, Ralph Birkenhead, 2008, ICANN.

A renewed approach to serious games for cyber security

David A. Elizondo, Tim Watson, Alexis Le Compte, 2015, 2015 7th International Conference on Cyber Conflict: Architectures in Cyberspace.

An Introduction to the Use of Neural Networks for Network Intrusion Detection

David A. Elizondo, Tim Watson, John North, 2012, Computational Intelligence for Privacy and Security.

Feature Selection of Hand Biometrical Traits Based on Computational Intelligence Techniques

Ezequiel López-Rubio, Esteban J. Palomo, David A. Elizondo, 2012, Computational Intelligence for Privacy and Security.

Estimation of classification complexity

David A. Elizondo, Matías Gámez, Ralph Birkenhead, 2009, 2009 International Joint Conference on Neural Networks.

Application of growing hierarchical SOM for visualisation of network forensics traffic data

Esteban J. Palomo, David A. Elizondo, Rafael Marcos Luque Baena, 2012, Neural Networks.

A fuzzy genetic programming-based algorithm for subgroup discovery and the application to one problem of pathogenesis of acute sore throat conditions in humans

María José del Jesús, David A. Elizondo, Cristóbal J. Carmona, 2015, Inf. Sci..

A Survey of Partially Connected Neural Networks

David A. Elizondo, Emile Fiesler, 1997, Int. J. Neural Syst..

Infering Air Quality from Traffic Data Using Transferable Neural Network Models

Miguel A. Molina-Cabello, David A. Elizondo, Enrique Domínguez, 2019, IWANN.

E2PAMEA: A fast evolutionary algorithm for extracting fuzzy emerging patterns in big data environments

David A. Elizondo, Ángel Miguel García-Vico, Francisco Charte, 2020, Neurocomputing.

Authentication of Individuals using Hand Geometry Biometrics: A Neural Network Approach

Miguel Angel Ferrer-Ballester, Marcos Faúndez-Zanuy, David A. Elizondo, 2007, Neural Processing Letters.

Natural language processing: a prolog perspective

David A. Elizondo, Yingjie Yang, Christian Bitter, 2010, Artificial Intelligence Review.

Evolutionary Computation in Computer Security and Forensics: An Overview

Sulaiman Al Amro, Agusti Solanas, David A. Elizondo, 2012, Computational Intelligence for Privacy and Security.

Light source detection for digital images in noisy scenes: a neural network approach

David A. Elizondo, Charalambos Chrysostomou, Shang-Ming Zhou, 2016, Neural Computing and Applications.

The recursive deterministic perceptron neural network

David A. Elizondo, Mohamed Tajine, 1998, Neural Networks.

Analysis and Testing of the m-Class RDP Neural Network

Juan Miguel Ortiz-de-Lazcano-Lobato, David A. Elizondo, Ralph Birkenhead, 2009, Constructive Neural Networks.

Application of artificial neural networks and related techniques to intrusion detection

David A. Elizondo, Tim Watson, Christian Bitter, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

The class of linear separability method

David A. Elizondo, Mohamed Tajine, Jerzy J. Korczak, 1997, ESANN.

Skin Lesion Classification by Ensembles of Deep Convolutional Networks and Regularly Spaced Shifting

Ezequiel López-Rubio, Karl Thurnhofer-Hemsi, David A. Elizondo, 2021, IEEE Access.

Fuzzy Logic Applied to System Monitors

Miguel A. Molina-Cabello, David A. Elizondo, Lipika Deka, 2021, IEEE Access.