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David A. Elizondo
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2020 – today
- 2024
- [j39]María Dolores Pérez-Godoy, Marta Molina, Francisco Martínez, David A. Elizondo, Francisco Charte, Antonio J. Rivera:
DESReg: Dynamic Ensemble Selection library for Regression tasks. Neurocomputing 580: 127487 (2024) - [j38]Bashar Alshouha
, Jesús Serrano-Guerrero
What is the Consumer Attitude toward Healthcare Services? A Transfer Learning Approach for Detecting Emotions from Consumer Feedback. J. Univers. Comput. Sci. 30(1): 3-24 (2024) - [i8]Anthony Kenyon, Lipika Deka, David A. Elizondo:
Characterising Payload Entropy in Packet Flows. CoRR abs/2404.19121 (2024) - 2023
- [j37]Antonio Jesús Rivera
XAIRE: An ensemble-based methodology for determining the relative importance of variables in regression tasks. Application to a hospital emergency department. Artif. Intell. Medicine 137: 102494 (2023) - [j36]Antonio J. Rivera, Miguel A. Dávila, David A. Elizondo, María José del Jesus, Francisco Charte
mldr.resampling: Efficient reference implementations of multilabel resampling algorithms. Neurocomputing 559: 126806 (2023) - [j35]J. M. Górriz
Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends. Inf. Fusion 100: 101945 (2023) - [j34]Ricardo Javier Fuentes-Fino, Saúl Calderón Ramírez
An uncertainty estimator method based on the application of feature density to classify mammograms for breast cancer detection. Neural Comput. Appl. 35(30): 22151-22161 (2023) - [j33]Saúl Calderón Ramírez
Dataset Similarity to Assess Semisupervised Learning Under Distribution Mismatch Between the Labeled and Unlabeled Datasets. IEEE Trans. Artif. Intell. 4(2): 282-291 (2023) - [c34]Maria Isabel Cabrera-Bermejo
Analysis of Transformer Model Applications. HAIS 2023: 231-243 - [i7]Antonio J. Rivera, Miguel A. Dávila, David A. Elizondo, María José del Jesus, Francisco Charte:
mldr.resampling: Efficient Reference Implementations of Multilabel Resampling Algorithms. CoRR abs/2305.17152 (2023) - [i6]Anthony Kenyon, David A. Elizondo, Lipika Deka:
Improved Flow Recovery from Packet Data. CoRR abs/2310.09834 (2023) - 2022
- [j32]Saúl Calderón Ramírez
Dealing with distribution mismatch in semi-supervised deep learning for COVID-19 detection using chest X-ray images: A novel approach using feature densities. Appl. Soft Comput. 123: 108983 (2022) - [j31]Francisco J. Moreno-Barea
Application of data augmentation techniques towards metabolomics. Comput. Biol. Medicine 148: 105916 (2022) - [j30]Antonio J. Rivera, María Dolores Pérez-Godoy, David A. Elizondo, Lipika Deka, María José del Jesus:
Analysis of clustering methods for crop type mapping using satellite imagery. Neurocomputing 492: 91-106 (2022) - [j29]Saúl Calderón Ramírez
A real use case of semi-supervised learning for mammogram classification in a local clinic of Costa Rica. Medical Biol. Eng. Comput. 60(4): 1159-1175 (2022) - [j28]Saúl Calderón Ramírez
Semisupervised Deep Learning for Image Classification With Distribution Mismatch: A Survey. IEEE Trans. Artif. Intell. 3(6): 1015-1029 (2022) - [c33]Francisco J. Moreno-Barea
Data Augmentation Techniques to Improve Metabolomic Analysis in Niemann-Pick Type C Disease. ICCS (3) 2022: 78-91 - [i5]Saúl Calderón Ramírez
Semi-supervised Deep Learning for Image Classification with Distribution Mismatch: A Survey. CoRR abs/2203.00190 (2022) - 2021
- [j27]Noel Khan
Fuzzy Logic Applied to System Monitors. IEEE Access 9: 56523-56538 (2021) - [j26]Saúl Calderón Ramírez
Improving Uncertainty Estimation With Semi-Supervised Deep Learning for COVID-19 Detection Using Chest X-Ray Images. IEEE Access 9: 85442-85454 (2021) - [j25]Karl Thurnhofer-Hemsi
Skin Lesion Classification by Ensembles of Deep Convolutional Networks and Regularly Spaced Shifting. IEEE Access 9: 112193-112205 (2021) - [j24]Saúl Calderón Ramírez
Correcting data imbalance for semi-supervised COVID-19 detection using X-ray chest images. Appl. Soft Comput. 111: 107692 (2021) - [j23]Juan Jesús Ruiz-Aguilar
A permutation entropy-based EMD-ANN forecasting ensemble approach for wind speed prediction. Neural Comput. Appl. 33(7): 2369-2391 (2021) - [c32]Saúl Calderón Ramírez
Improving Uncertainty Estimations for Mammogram Classification using Semi-Supervised Learning. IJCNN 2021: 1-8 - [c31]Willard Zamora-Cárdenas, Mauro Mendez
Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images. IWANN (1) 2021: 36-46 - [i4]Willard Zamora-Cárdenas, Mauro Mendez, Saúl Calderón Ramírez, Martin Vargas, Gerardo Monge, Steve Quirós, David A. Elizondo, Miguel A. Molina-Cabello:
Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images. CoRR abs/2106.05843 (2021) - [i3]Saúl Calderón Ramírez, Diego Murillo-Hernandez, Kevin Rojas-Salazar, David A. Elizondo, Shengxiang Yang, Miguel A. Molina-Cabello:
A Real Use Case of Semi-Supervised Learning for Mammogram Classification in a Local Clinic of Costa Rica. CoRR abs/2107.11696 (2021) - [i2]Saúl Calderón Ramírez, Shengxiang Yang, David A. Elizondo, Armaghan Moemeni:
Dealing with Distribution Mismatch in Semi-supervised Deep Learning for Covid-19 Detection Using Chest X-ray Images: A Novel Approach Using Feature Densities. CoRR abs/2109.00889 (2021) - 2020
- [j22]Miguel A. Molina-Cabello
Aggregation of Convolutional Neural Network Estimations of Homographies by Color Transformations of the Inputs. IEEE Access 8: 79552-79560 (2020) - [j21]Anthony Kenyon, Lipika Deka
Are public intrusion datasets fit for purpose characterising the state of the art in intrusion event datasets. Comput. Secur. 99: 102022 (2020) - [j20]Miguel A. Molina-Cabello
Foreground detection by ensembles of random polygonal tilings. Expert Syst. Appl. 161: 113518 (2020) - [j19]Ángel Miguel García-Vico, Francisco Charte, Pedro González
E2PAMEA: A fast evolutionary algorithm for extracting fuzzy emerging patterns in big data environments. Neurocomputing 415: 60-73 (2020) - [c30]Saúl Calderón Ramírez
Dealing with Scarce Labelled Data: Semi-supervised Deep Learning with Mix Match for Covid-19 Detection Using Chest X-ray Images. ICPR 2020: 5294-5301 - [c29]Antonio Jesús Rivera, María Dolores Pérez-Godoy, David A. Elizondo, Lipika Deka
A Preliminary Study on Crop Classification with Unsupervised Algorithms for Time Series on Images with Olive Trees and Cereal Crops. SOCO 2020: 276-285 - [i1]Saúl Calderón Ramírez, Shengxiang Yang, Armaghan Moemeni, David A. Elizondo, Simon Colreavy-Donnelly, Luis Fernando Chavarria-Estrada, Miguel A. Molina-Cabello:
Correcting Data Imbalance for Semi-Supervised Covid-19 Detection Using X-ray Chest Images. CoRR abs/2008.08496 (2020)
2010 – 2019
- 2019
- [c28]Oskar Wysocki, Lipika Deka
Heavy duty vehicle fuel consumption modeling using artificial neural networks. ICAC 2019: 1-6 - [c27]Oskar Wysocki
Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks. IWANN (1) 2019: 794-805 - [c26]Miguel A. Molina-Cabello, Benjamin N. Passow, Enrique Domínguez, David A. Elizondo, Jolanta Obszynska:
Infering Air Quality from Traffic Data Using Transferable Neural Network Models. IWANN (1) 2019: 832-843 - 2017
- [j18]David A. Elizondo, Shang-Ming Zhou
Light source detection for digital images in noisy scenes: a neural network approach. Neural Comput. Appl. 28(5): 899-909 (2017) - [c25]Noel Khan, David A. Elizondo, Benjamin N. Passow, Pamela A. Hardaker:
Pose invariance through registration for hierarchical feature based pattern recognition systems. IJCNN 2017: 2902-2910 - 2016
- [c24]Frédéric Magoulès
Support Vector Regression for Electricity Consumption Prediction in a Building in Japan. CSE/EUC/DCABES 2016: 189-196 - 2015
- [j17]Ezequiel López-Rubio
Computational Intelligence Techniques in Medicine. Comput. Math. Methods Medicine 2015: 196976:1-196976:2 (2015) - [j16]Cristóbal J. Carmona
A fuzzy genetic programming-based algorithm for subgroup discovery and the application to one problem of pathogenesis of acute sore throat conditions in humans. Inf. Sci. 298: 180-197 (2015) - [c23]Alexis Le Compte, David A. Elizondo, Tim Watson:
A renewed approach to serious games for cyber security. CyCon 2015: 203-216 - 2014
- [c22]Pamela A. Hardaker, Benjamin N. Passow, David A. Elizondo:
Multiple sensor outputs and computational intelligence towards estimating state and speed for control of lower limb prostheses. UKCI 2014: 1-8 - 2013
- [j15]Rafael M. Luque-Baena
Assessment of geometric features for individual identification and verification in biometric hand systems. Expert Syst. Appl. 40(9): 3580-3594 (2013) - [j14]David A. Elizondo, Robert Morris, Tim Watson, Benjamin N. Passow:
Constructive Recursive Deterministic Perceptron Neural Networks with Genetic Algorithms. Int. J. Pattern Recognit. Artif. Intell. 27(6) (2013) - [j13]Derong Liu
Editorial A Successful Change From TNN to TNNLS and a Very Successful Year. IEEE Trans. Neural Networks Learn. Syst. 24(1): 1-7 (2013) - [c21]Benjamin N. Passow, David A. Elizondo, Francisco Chiclana
Adapting traffic simulation for traffic management: A neural network approach. ITSC 2013: 1402-1407 - [c20]Pamela A. Hardaker, Benjamin N. Passow, David A. Elizondo:
State detection from electromyographic signals towards the control of prosthetic limbs. UKCI 2013: 120-127 - 2012
- [j12]David A. Elizondo, Ralph Birkenhead, Matías Gámez, Noelia García Rubio
Linear separability and classification complexity. Expert Syst. Appl. 39(9): 7796-7807 (2012) - [j11]Esteban J. Palomo
Application of growing hierarchical SOM for visualisation of network forensics traffic data. Neural Networks 32: 275-284 (2012) - [c19]Sylvain Contassot-Vivier, David A. Elizondo:
A Near Linear Algorithm for Testing Linear Separability in Two Dimensions. EANN 2012: 114-124 - [p10]David A. Elizondo, Agusti Solanas
Computational Intelligence for Privacy and Security: Introduction. Computational Intelligence for Privacy and Security 2012: 1-4 - [p9]Christian Bitter, John North, David A. Elizondo, Tim Watson:
An Introduction to the Use of Neural Networks for Network Intrusion Detection. Computational Intelligence for Privacy and Security 2012: 5-24 - [p8]Sulaiman Al Amro, David A. Elizondo, Agusti Solanas
Evolutionary Computation in Computer Security and Forensics: An Overview. Computational Intelligence for Privacy and Security 2012: 25-34 - [p7]Sulaiman Al Amro, Francisco Chiclana
Application of Fuzzy Logic in Computer Security and Forensics. Computational Intelligence for Privacy and Security 2012: 35-49 - [p6]Esteban J. Palomo
SOM-Based Techniques towards Hierarchical Visualisation of Network Forensics Traffic Data. Computational Intelligence for Privacy and Security 2012: 75-95 - [p5]Rafael Marcos Luque
Feature Selection of Hand Biometrical Traits Based on Computational Intelligence Techniques. Computational Intelligence for Privacy and Security 2012: 159-180 - [p4]Bernd Carsten Stahl
Intelligence Techniques in Computer Security and Forensics: At the Boundaries of Ethics and Law. Computational Intelligence for Privacy and Security 2012: 237-258 - [e2]David A. Elizondo, Agusti Solanas, Antoni Martínez-Ballesté:
Computational Intelligence for Privacy and Security. Studies in Computational Intelligence 394, Springer 2012, ISBN 978-3-642-25236-5 [contents] - 2011
- [j10]David A. Elizondo, Juan Miguel Ortiz-de-Lazcano-Lobato
Choice effect of linear separability testing methods on constructive neural network algorithms: An empirical study. Expert Syst. Appl. 38(3): 2330-2346 (2011) - [c18]Rafael Marcos Luque
GA-based feature selection approach in biometric hand systems. IJCNN 2011: 246-253 - [c17]Esteban J. Palomo
Visualisation of network forensics traffic data with a self-organising map for qualitative features. IJCNN 2011: 1740-1747 - 2010
- [j9]Christian Bitter, David A. Elizondo, Yingjie Yang:
Natural language processing: a prolog perspective. Artif. Intell. Rev. 33(1-2): 151-173 (2010) - [c16]Christian Bitter, David A. Elizondo, Tim Watson:
Application of artificial neural networks and related techniques to intrusion detection. IJCNN 2010: 1-8 - [c15]Andreas Huemer, Mario Gongora
A robust reinforcement based self constructing neural network. IJCNN 2010: 1-7 - [c14]Bernd Carsten Stahl
Ethical and legal issues of the use of computational intelligence techniques in computer security and computer forensics. IJCNN 2010: 1-8
2000 – 2009
- 2009
- [c13]David A. Elizondo, Ralph Birkenhead, Matías Gámez, Noelia García Rubio
Estimation of classification complexity. IJCNN 2009: 764-770 - [p3]Maria do Carmo Nicoletti, João Roberto Bertini Jr., David A. Elizondo, Leonardo Franco
Constructive Neural Network Algorithms for Feedforward Architectures Suitable for Classification Tasks. Constructive Neural Networks 2009: 1-23 - [p2]David A. Elizondo, Juan Miguel Ortiz-de-Lazcano-Lobato
Analysis and Testing of the m-Class RDP Neural Network. Constructive Neural Networks 2009: 171-192 - [p1]Andreas Huemer, David A. Elizondo, Mario Gongora
A Constructive Neural Network for Evolving a Machine Controller in Real-Time. Constructive Neural Networks 2009: 225-242 - [e1]Leonardo Franco, David A. Elizondo, José M. Jerez:
Constructive Neural Networks. Studies in Computational Intelligence 258, Springer 2009, ISBN 978-3-642-04511-0 [contents] - 2008
- [j8]Esteban Alfaro Cortés
Bankruptcy forecasting: An empirical comparison of AdaBoost and neural networks. Decis. Support Syst. 45(1): 110-122 (2008) - [c12]David A. Elizondo, Juan Miguel Ortiz-de-Lazcano-Lobato
On the Generalization of the m-Class RDP Neural Network. ICANN (2) 2008: 734-743 - [c11]Andreas Huemer, David A. Elizondo, Mario Gongora:
A Reward-Value Based Constructive Method for the Autonomous Creation of Machine Controllers. ICANN (2) 2008: 773-782 - [c10]David A. Elizondo, Shang-Ming Zhou
Surface Reconstruction Techniques Using Neural Networks to Recover Noisy 3D Scenes. ICANN (1) 2008: 857-866 - [c9]Andreas Huemer, Mario Gongora, David A. Elizondo:
Self Constructing Neural Network Robot Controller based on On-line Task Performance Feedback. ICINCO-ICSO 2008: 326-333 - [c8]Andreas Huemer, Mario Gongora, David A. Elizondo:
Evolving a neural network using dyadic connections. IJCNN 2008: 1019-1025 - 2007
- [j7]David A. Elizondo, Ralph Birkenhead, Mario Gongora, Éric D. Taillard, Patrick Luyima:
Analysis and test of efficient methods for building recursive deterministic perceptron neural networks. Neural Networks 20(10): 1095-1108 (2007) - [j6]Marcos Faúndez-Zanuy
Authentication of Individuals using Hand Geometry Biometrics: A Neural Network Approach. Neural Process. Lett. 26(3): 201-216 (2007) - [c7]David A. Elizondo, Juan Miguel Ortiz-de-Lazcano-Lobato, Ralph Birkenhead:
A Novel and Efficient Method for Testing Non Linear Separability. ICANN (1) 2007: 737-746 - 2006
- [j5]David A. Elizondo:
The linear separability problem: some testing methods. IEEE Trans. Neural Networks 17(2): 330-344 (2006) - [c6]David A. Elizondo, Ralph Birkenhead, Éric D. Taillard:
The Generalisation of the Recursive Deterministic Perceptron. IJCNN 2006: 1776-1783 - 2005
- [c5]David A. Elizondo, Mario Gongora:
Current Trends on Knowledge Extraction and Neural Networks. ICANN (2) 2005: 485-490 - [c4]Mario Gongora, Tim Watson, David A. Elizondo:
A Novel Method for Extracting Knowledge from Neural Networks with Evolving SQL Queries. ICANN (2) 2005: 497-502 - 2002
- [j4]Mohamed Tajine, David A. Elizondo:
New methods for testing linear separability. Neurocomputing 47(1-4): 161-188 (2002)
1990 – 1999
- 1998
- [j3]Mohamed Tajine, David A. Elizondo:
Growing Methods for Constructing Recursive Deterministic Perceptron Neural Networks and Knowledge Extraction. Artif. Intell. 102(2): 295-322 (1998) - [j2]Mohamed Tajine, David A. Elizondo:
The recursive deterministic perceptron neural network. Neural Networks 11(9): 1571-1588 (1998) - 1997
- [j1]David A. Elizondo, Emile Fiesler:
A Survey of Partially Connected Neural Networks. Int. J. Neural Syst. 8(5-6): 535-558 (1997) - [c3]Mohamed Tajine, David A. Elizondo, Emile Fiesler, Jerzy Korczak:
The class of linear separability method. ESANN 1997 - [c2]Mohamed Tajine, David A. Elizondo, Emile Fiesler, Jerzy Korczak
Adapting the 2-class recursive deterministic perceptron neural network to m-classes. ICNN 1997: 1542-1546 - 1995
- [c1]David A. Elizondo, Emile Fiesler, Jerzy Korczak:
Non-ontogenic sparse neural networks. ICNN 1995: 290-295
Coauthor Index
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last updated on 2024-10-07 22:09 CEST by the dblp team
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