Publicaciones en las que colabora con Jorge García Gutiérrez (11)

2019

  1. On the evolutionary weighting of neighbours and features in the k-nearest neighbour rule

    Neurocomputing, Vol. 326-327, pp. 54-60

2016

  1. A preliminary study of the suitability of deep learning to improve LiDAR-derived biomass estimation

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

  2. An evolutionary voting for k-nearest neighbours

    Expert Systems with Applications, Vol. 43, pp. 9-14

2015

  1. An evolutionary-weighted majority voting and support vector machines applied to contextual classification of LiDAR and imagery data fusion

    Neurocomputing, Vol. 163, pp. 17-24

2014

  1. Improving the k-nearest neighbour rule by an evolutionary voting approach

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

2012

  1. A non-parametric approach for accurate contextual classification of LIDAR and imagery data fusion

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

  2. EVOR-STACK: A label-dependent evolutive stacking on remote sensing data fusion

    Neurocomputing, Vol. 75, Núm. 1, pp. 115-122

  3. On the evolutionary optimization of k-NN by label-dependent feature weighting

    Pattern Recognition Letters, Vol. 33, Núm. 16, pp. 2232-2238

2011

  1. A comparative study between two regression methods on LiDAR data: A case study

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

2010

  1. A SVM and k-NN restricted stacking to improve land use and land cover classification

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

  2. Label dependent evolutionary feature weighting for remote sensing data

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