José Manuel Palomares Muñoz-rekin lankidetzan egindako argitalpenak (13)

2022

  1. A Preliminary Fuzzy Markup Language based Approach for the Queue Buffer Size Optimization in Fog Nodes for Stream Processing

    IEEE International Conference on Fuzzy Systems

2013

  1. The use of video-gaming devices as a motivation for learning embedded systems programming

    IEEE Transactions on Education, Vol. 56, Núm. 2, pp. 199-207

2011

  1. Learning FPGA design by a methodology based on projects

    The International journal of engineering education, Vol. 27, Núm. 3, pp. 509-517

  2. Learning FPGA design by a methodology based on projects

    International Journal of Engineering Education, Vol. 27, Núm. 3 PART 1, pp. 509-517

2010

  1. License plate detection based on genetic neural networks, morphology, and active contours

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Teaching microprocessors design using FPGAs

    2010 IEEE Education Engineering Conference, EDUCON 2010

2009

  1. Experiencia de una metodología basada en proyectos para asignaturas de Ingeniería

    1.as Jornadas andaluzas de innovación docente universitaria: 2 y 3 de diciembre de 2009, Córdoba

2007

  1. Improving the accuracy while preserving the interpretability of fuzzy function approximators by means of multi-objective evolutionary algorithms

    International Journal of Approximate Reasoning, Vol. 44, Núm. 1, pp. 32-44

2006

  1. General logarithmic image processing convolution

    IEEE Transactions on Image Processing, Vol. 15, Núm. 11, pp. 3602-3608

  2. Multi-objective evolution of fuzzy systems

    Soft Computing, Vol. 10, Núm. 9, pp. 735-748

  3. Skin lesion diagnosis using fluorescence images

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2005

  1. Designing a fast convolution under the LIP paradigm applied to edge detection

    Lecture Notes in Computer Science

  2. Designing a fast convolution under the LIP paradigm applied to edge detection

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)