The SCEAS System
Navigation Menu

Search the dblp DataBase

Title:
Author:

José M. Molina: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Javier Ignacio Carbó Rubiera, Jesús García, José M. Molina
    Subjective Trust Inferred by Kalman Filtering vs. a Fuzzy Reputation. [Citation Graph (0, 0)][DBLP]
    ER (Workshops), 2004, pp:496-505 [Conf]
  2. Óscar Pérez, Jesús García, Antonio Berlanga, José M. Molina
    Evolving Parameters of Surveillance Video Systems for Non-overfitted Learning. [Citation Graph (0, 0)][DBLP]
    EvoWorkshops, 2005, pp:386-395 [Conf]
  3. Óscar Pérez, Miguel Ángel Patricio Guisado, Jesús García, José M. Molina
    Improving the Segmentation Stage of a Pedestrian Tracking Video-Based System by Means of Evolution Strategies. [Citation Graph (0, 0)][DBLP]
    EvoWorkshops, 2006, pp:438-449 [Conf]
  4. Antonio Berlanga, Pedro Isasi, Araceli Sanchis de Miguel, José M. Molina
    Uniform Coevolution for solving the density classification problem in Cellular Automata. [Citation Graph (0, 0)][DBLP]
    GECCO, 2000, pp:383- [Conf]
  5. Germán Gutiérrez, Inés María Galván, José M. Molina, Araceli Sanchís
    Generative Capacities of Cellular Automata Codification for Evolution of NN Codification. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:314-322 [Conf]
  6. F. Castanedo, Miguel Ángel Patricio Guisado, José M. Molina
    Evolutionary Computation Technique Applied to HSPF Model Calibration of a Spanish Watershed. [Citation Graph (0, 0)][DBLP]
    IDEAL, 2006, pp:216-223 [Conf]
  7. David Camacho, José M. Molina, Daniel Borrajo, Ricardo Aler
    Solving Travel Problems by Integrating WEB Information with Planning. [Citation Graph (0, 0)][DBLP]
    ISMIS, 2002, pp:482-490 [Conf]
  8. Antonio Berlanga, José M. Molina, Araceli Sanchís, Pedro Isasi
    Applying Evolution Strategies to Neural Networks Robot Controller. [Citation Graph (0, 0)][DBLP]
    IWANN (2), 1999, pp:516-525 [Conf]
  9. Germán Gutiérrez, Beatriz García, José M. Molina, Araceli Sanchís
    Studying the Capacity of Grammatical Encoding to Generate FNN Architectures. [Citation Graph (0, 0)][DBLP]
    IWANN (1), 2003, pp:478-485 [Conf]
  10. German Gutiérrez Sanchez, Pedro Isasi, José M. Molina, Araceli Sanchís, Inés María Galván
    Evolutionary Cellular Configurations for Designing Feed-Forward Neural Networks Architectures. [Citation Graph (0, 0)][DBLP]
    IWANN (1), 2001, pp:514-521 [Conf]
  11. José M. Molina, Jesús García, Javier de Diego, Javier I. Portillo
    Neuro-fuzzy Techniques for Image Tracking. [Citation Graph (0, 0)][DBLP]
    IWANN (2), 2003, pp:504-511 [Conf]
  12. Araceli Sanchís, José M. Molina, Pedro Isasi, Javier Segovia
    Learning Symbolic Rules with a Reactive with Tags Classifier System in Robot Navigation. [Citation Graph (0, 0)][DBLP]
    IWANN (2), 1999, pp:548-557 [Conf]
  13. Óscar Pérez, Jesús García, Antonio Berlanga, José M. Molina
    Adjustment of Surveillance Video Systems by a Performance Evaluation Function. [Citation Graph (0, 0)][DBLP]
    IWINAC (2), 2005, pp:499-508 [Conf]
  14. Blanca Rodríguez, Óscar Pérez, Jesús García, José M. Molina
    Application of Machine Learning Techniques for Simplifying the Association Problem in a Video Surveillance System. [Citation Graph (0, 0)][DBLP]
    IWINAC (2), 2005, pp:509-518 [Conf]
  15. Óscar Pérez, Jesús García, José M. Molina
    Neuro-fuzzy Learning Applied to Improve the Trajectory Reconstruction Problem. [Citation Graph (0, 0)][DBLP]
    CIMCA/IAWTIC, 2006, pp:4- [Conf]
  16. David Camacho, Daniel Borrajo, José M. Molina
    Intelligent Travel Planning: A MultiAgent Planning System to Solve Web Problems in the e-Tourism Domain. [Citation Graph (0, 0)][DBLP]
    Autonomous Agents and Multi-Agent Systems, 2001, v:4, n:4, pp:387-392 [Journal]
  17. M. A. Guinea, Araceli Sanchís, José M. Molina
    Evolución de gramáticas bidimensionales de contexto libre para el diseño de arquitecturas de redes de neuronas artificiales. [Citation Graph (0, 0)][DBLP]
    Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial, 2002, v:17, n:, pp:33-48 [Journal]
  18. Araceli Sanchís, José M. Molina, Pedro Isasi, Javier Segovia
    Generación Automática de Categorias mediante la Evoluciónde Tags en Sistemas Clasificadores. [Citation Graph (0, 0)][DBLP]
    Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial, 1999, v:7, n:, pp:77-97 [Journal]
  19. José María Valls, José M. Molina, Inés María Galván
    Sistema Multiagente para el diseño de Redes de Neuronas de Base Radial Óptimas. [Citation Graph (0, 0)][DBLP]
    Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial, 2000, v:10, n:, pp:18-25 [Journal]
  20. David Camacho, Ricardo Aler, Daniel Borrajo, José M. Molina
    A Multi-Agent architecture for intelligent gathering systems. [Citation Graph (0, 0)][DBLP]
    AI Commun., 2005, v:18, n:1, pp:15-32 [Journal]
  21. Javier Ignacio Carbó Rubiera, José M. Molina, Jorge Dávila Muro
    Fuzzy referral based cooperation in social networks of agents. [Citation Graph (0, 0)][DBLP]
    AI Commun., 2005, v:18, n:1, pp:1-13 [Journal]
  22. Jesús García, Antonio Berlanga, José M. Molina, José R. Casar
    Optimization of airport ground operations integrating genetic and dynamic flow management algorithms. [Citation Graph (0, 0)][DBLP]
    AI Commun., 2005, v:18, n:2, pp:143-164 [Journal]
  23. David Camacho, Ricardo Aler, Daniel Borrajo, José M. Molina
    Multi-agent plan based information gathering. [Citation Graph (0, 0)][DBLP]
    Appl. Intell., 2006, v:25, n:1, pp:59-71 [Journal]
  24. Pedro Isasi, Araceli Sanchís, José M. Molina, Antonio Berlanga
    A Computational Model of Evolution: Haploidy versus Diploidy. [Citation Graph (0, 0)][DBLP]
    Computers and Artificial Intelligence, 1999, v:18, n:6, pp:- [Journal]
  25. José M. Molina, Inés María Galván, José María Valls, Andrés Leal
    Optimizing the Number of Learning Cycles in the Design of Radial Basis Neural Networks Using a Multi-Agent System. [Citation Graph (0, 0)][DBLP]
    Computers and Artificial Intelligence, 2001, v:20, n:5, pp:- [Journal]
  26. Germán Gutiérrez, Araceli Sanchís, Pedro Isasi Viñuela, José M. Molina, Inés María Galván
    Non-Direct Encoding Method Based on Cellular Automata to Design Neural Network Architectures. [Citation Graph (0, 0)][DBLP]
    Computers and Artificial Intelligence, 2005, v:24, n:3, pp:- [Journal]
  27. Javier Ignacio Carbó Rubiera, José M. Molina, Jorge Dávila Muro
    Trust Management Through Fuzzy Reputation. [Citation Graph (0, 0)][DBLP]
    Int. J. Cooperative Inf. Syst., 2003, v:12, n:1, pp:135-155 [Journal]
  28. Javier Ignacio Carbó Rubiera, José M. Molina
    Agent-based collaborative filtering based on fuzzy recommendations. [Citation Graph (0, 0)][DBLP]
    Int. J. Web Eng. Technol., 2004, v:1, n:4, pp:414-426 [Journal]
  29. J. A. Besada, José M. Molina, Jesús García, Antonio Berlanga, Javier I. Portillo
    Aircraft identification integrated into an airport surface surveillance video system. [Citation Graph (0, 0)][DBLP]
    Mach. Vis. Appl., 2004, v:15, n:3, pp:164-171 [Journal]
  30. Miguel Ángel Patricio Guisado, Jesús García, Antonio Berlanga, José M. Molina
    Video Tracking Association Problem Using Estimation of Distribution Algorithms in Complex Scenes. [Citation Graph (0, 0)][DBLP]
    IWINAC (2), 2007, pp:261-270 [Conf]
  31. Óscar Pérez, Massimo Piccardi, Jesús García, José M. Molina
    Comparison of Classifiers for Human Activity Recognition. [Citation Graph (0, 0)][DBLP]
    IWINAC (2), 2007, pp:192-201 [Conf]
  32. A. M. Sánchez, M. A. Patricio, J. García, J. M. Molina
    Context Data to Improve Association in Visual Tracking Systems. [Citation Graph (0, 0)][DBLP]
    IWINAC (2), 2007, pp:212-221 [Conf]
  33. Jesús García, Antonio Berlanga, José M. Molina
    Evolutionary algorithms in multiply-specified engineering. The MOEAs and WCES strategies. [Citation Graph (0, 0)][DBLP]
    Advanced Engineering Informatics, 2007, v:21, n:1, pp:3-21 [Journal]
  34. Jesús García, Javier Carbó, José M. Molina
    Agent-based Coordination of Cameras. [Citation Graph (0, 0)][DBLP]
    IJCSA, 2005, v:2, n:1, pp:33-37 [Journal]

  35. Context-Based Reasoning Using Ontologies to Adapt Visual Tracking in Surveillance. [Citation Graph (, )][DBLP]


  36. Creating Human Activity Recognition Systems Using Pareto-based Multiobjective Optimization. [Citation Graph (, )][DBLP]


  37. Bottom-up/top-down coordination in a multiagent visual sensor network. [Citation Graph (, )][DBLP]


  38. Scalable Continuous Multiobjective Optimization with a Neural Network-Based Estimation of Distribution Algorithm. [Citation Graph (, )][DBLP]


  39. Advancing Model-Building for Many-Objective Optimization Estimation of Distribution Algorithms. [Citation Graph (, )][DBLP]


  40. Solving complex high-dimensional problems with the multi-objective neural estimation of distribution algorithm. [Citation Graph (, )][DBLP]


  41. Moving away from error-based learning in multi-objective estimation of distribution algorithms. [Citation Graph (, )][DBLP]


  42. Context-Aware Approach for Orally Accessible Web Services. [Citation Graph (, )][DBLP]


  43. Optimised Particle Filter Approaches to Object Tracking in Video Sequences. [Citation Graph (, )][DBLP]


  44. Towards Interoperability in Tracking Systems: An Ontology-Based Approach. [Citation Graph (, )][DBLP]


  45. Solving video-association problem with explicit evaluation of hypothesis using EDAs. [Citation Graph (, )][DBLP]


  46. Learning User Profile with Genetic Algorithm in AmI Applications. [Citation Graph (, )][DBLP]


  47. On the Model-Building Issue of Multi-Objective Estimation of Distribution Algorithms. [Citation Graph (, )][DBLP]


  48. Fusion of Single View Soft k-NN Classifiers for Multicamera Human Action Recognition. [Citation Graph (, )][DBLP]


  49. Requirements for Supervised Fusion Adaption at Level 1 of JDL Data Fusion Model, . [Citation Graph (, )][DBLP]


  50. On the Process of Designing an Activity Recognition System Using Symbolic and Subsymbolic Techniques. [Citation Graph (, )][DBLP]


  51. Advanced algorithms for real-time video tracking with multiple targets. [Citation Graph (, )][DBLP]


  52. On the Computational Properties of the Multi-Objective Neural Estimation of Distribution Algorithm. [Citation Graph (, )][DBLP]


  53. Designing a Visual Sensor Network Using a Multi-agent Architecture. [Citation Graph (, )][DBLP]


  54. An Architecture for the Design of Context-Aware Conversational Agents. [Citation Graph (, )][DBLP]


  55. Discrete Optimization Algorithms in Real-Time Visual Tracking. [Citation Graph (, )][DBLP]


  56. Machine Learning Techniques for Acquiring New Knowledge in Image Tracking. [Citation Graph (, )][DBLP]


Search in 0.003secs, Finished in 0.493secs
NOTICE1
System may not be available sometimes or not working properly, since it is still in development with continuous upgrades
NOTICE2
The rankings that are presented on this page should NOT be considered as formal since the citation info is incomplete in DBLP
 
System created by asidirop@csd.auth.gr [http://users.auth.gr/~asidirop/] © 2002
for Data Engineering Laboratory, Department of Informatics, Aristotle University © 2002