Publicaciones en colaboración con investigadores/as de Universidade de Santiago de Compostela (26)

2019

  1. Design of fuzzy controllers for embedded systems with JFML

    International Journal of Computational Intelligence Systems, Vol. 12, Núm. 1, pp. 204-214

  2. Does social network sentiment influence S & P 500 Environmental & Socially Responsible Index?

    Sustainability (Switzerland), Vol. 11, Núm. 2

  3. Py4JFML: A Python wrapper for using the IEEE Std 1855-2016 through JFML

    IEEE International Conference on Fuzzy Systems

2018

  1. Design of Fuzzy Controllers for Embedded Systems With JFML

    International Journal of Computational Intelligence Systems, Vol. 12, Núm. 1, pp. 204-214

  2. JFML: A Java library to design fuzzy logic systems according to the IEEE Std 1855-2016

    IEEE Access, Vol. 6, pp. 56952-56964

2003

  1. Best achievable compression ratio for lossy image coding

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 2652, pp. 263-270

  2. CORAL: Collective rationality for the allocation of bits

    Optical Engineering, Vol. 42, Núm. 4, pp. 1000-1012

  3. On the concept of best achievable compression ratio for lossy image coding

    Pattern Recognition, Vol. 36, Núm. 10, pp. 2377-2394

2002

  1. Coder selection for lossy compression of still images

    Pattern Recognition, Vol. 35, Núm. 11, pp. 2489-2509

  2. Optimized rate control in embedded wavelet coding

    Proceedings - International Conference on Pattern Recognition

  3. Performance of the Kullback-Leibler information gain for predicting image fidelity

    Proceedings - International Conference on Pattern Recognition

2001

  1. Information theoretic measure for visual target distinctness

    IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, Núm. 4, pp. 362-383

  2. Minimum error gain for predicting visual target distinctness

    Optical Engineering, Vol. 40, Núm. 9, pp. 1794-1817

2000

  1. Computing visual target distinctness through selective filtering, statistical features, and visual patterns

    Optical Engineering, Vol. 39, Núm. 1, pp. 267-281

  2. Defining the notion of visual pattern for predicting visual target distinctness in a complex rural background

    Optical Engineering, Vol. 39, Núm. 2, pp. 415-429

  3. How to define the notion of microcalcifications in digitized mammograms

    Proceedings - International Conference on Pattern Recognition, Vol. 15, Núm. 1, pp. 494-499

  4. Image representational model for predicting visual distinctness of objects

    Proceedings - International Conference on Pattern Recognition, Vol. 15, Núm. 1, pp. 689-694

  5. Image representational model for predicting visual distinctness of objects

    15TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 1, PROCEEDINGS

  6. Integral opponent-colors features for computing visual target distinctness

    Pattern Recognition, Vol. 33, Núm. 7, pp. 1179-1198

  7. Origins of illusory percepts in digital images

    Pattern Recognition, Vol. 33, Núm. 12, pp. 2007-2017