Publicaciones en las que colabora con JUAN JOSE DEL COZ VELASCO (38)

2019

  1. Automatic plankton quantification using deep features

    Journal of Plankton Research, Vol. 41, Núm. 4, pp. 449-463

2018

  1. Deep Learning and Preference Learning for Object Tracking: A Combined Approach

    Neural Processing Letters, Vol. 47, Núm. 3, pp. 859-876

2017

  1. Deep learning to frame objects for visual target tracking

    Engineering Applications of Artificial Intelligence, Vol. 65, pp. 406-420

  2. Validation methods for plankton image classification systems

    Limnology and Oceanography: Methods, Vol. 15, Núm. 3, pp. 221-237

  3. Why is quantification an interesting learning problem?

    Progress in Artificial Intelligence, Vol. 6, Núm. 1, pp. 53-58

2016

  1. Combining deep learning and preference learning for object tracking

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

  2. El deprendizax automáticu computacional na valoración d'exemplares bovinos d'Asturiana de los Valles

    Ciencies. Cartafueyos Asturianos de Ciencia y Teunoloxía: Revista de la Academia de la Llingua Asturiana, Núm. 6, pp. 46-61

  3. Using tensor products to detect unconditional label dependence in multilabel classifications

    Information Sciences, Vol. 329, pp. 20-32

2015

  1. Optimizing different loss functions in multilabel classifications

    Progress in Artificial Intelligence, Vol. 3, Núm. 2, pp. 107-118

  2. Quantification-oriented learning based on reliable classifiers

    Pattern Recognition, Vol. 48, Núm. 2, pp. 591-604

2013

  1. Enhancing directed binary trees for multi-class classification

    Information Sciences, Vol. 223, pp. 42-55

  2. Multiclass support vector machines with example-dependent costs applied to plankton biomass estimation

    IEEE Transactions on Neural Networks and Learning Systems, Vol. 24, Núm. 11, pp. 1901-1905

  3. On the study of nearest neighbor algorithms for prevalence estimation in binary problems

    Pattern Recognition, Vol. 46, Núm. 2, pp. 472-482

  4. Predicting fertility from seminal traits: Performance of several parametric and non-parametric procedures

    Livestock Science, Vol. 155, Núm. 1, pp. 137-147

2012

  1. Binary relevance efficacy for multilabel classification

    Progress in Artificial Intelligence, Vol. 1, Núm. 4, pp. 303-313

  2. Learning data structure from classes: A case study applied to population genetics

    Information Sciences, Vol. 193, pp. 22-35

2010

  1. A semi-dependent decomposition approach to learn hierarchical classifiers

    Pattern Recognition, Vol. 43, Núm. 11, pp. 3795-3804

  2. Explaining the genetic basis of complex quantitative traits through prediction models

    Journal of Computational Biology, Vol. 17, Núm. 12, pp. 1711-1723

2009

  1. Learning nondeterministic classifiers

    Journal of Machine Learning Research, Vol. 10, pp. 2273-2293

  2. Prediction and inheritance of phenotypes

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