1. 2017
  2. A Compact Representation of Multiscale Dissimilarity Data by Prototype Selection

    Plasencia-Calaña, Y., Li, Y., Duin, R. P. W., Orozco-Alzate, M., Loog, M. & García-Reyes, E., 2017, Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 21st Iberoamerican Congress, CIARP 2016, Proceedings. Beltrán-Castañón, C., Nyström, I. & Famili, F. (eds.). Cham: Springer, p. 150-157 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10125 LNCS).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  3. 2016
  4. Pattern Recognition: Introduction and Terminology

    Duin, R. P. W. & Pekalska, E., 23 Aug 2016, Delft: Delft University of Technology. 77 p.

    Research output: Book/ReportBookScientific

  5. Beyond Condition-Monitoring: Comparing Diagnostic Events with Word Sequence Kernel for Train Delay Prediction

    Lee, W-J., Tax, D. & Duin, B., 2016, Proceedings of the Thord European Conference of the Prognostics and Health Management Society 2016. Eballard, I. & Bregon, A. (eds.). PHM Society, Vol. 7. p. 162-167 6 p.

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  6. The Similarity Between Dissimilarities

    Tax, D., Cheplygina, V., Duin, B. & van de Poll, J., 2016, Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshop, S+SSPR 2016, proceedings. Robles-Kelly, A., Loog, M., Biggio, B., Escolano, F. & Wilson, R. (eds.). Cham: Springer, p. 84-94 11 p. (Lecture Notes in Computer Science; vol. 10029).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  7. 2015
  8. The dissimilarity representation for finding universals from particulars by an anti-essentialist approach

    Duin, RPW., 2015, In : Pattern Recognition Letters. 64, October, p. 37-43 7 p.

    Research output: Contribution to journalArticleScientificpeer-review

  9. 2014
  10. Metric learning in dissimilarity space for improved nearest neighbor performance

    Duin, RPW., Bicego, M., Orozco-Alzate, M., Kim, S-W. & Loog, M., 2014, Proceedings of the Joint IAPR International Workshop, S+SSPR 2014. Fränti, P., Brown, G., Loog, M., Escolano, F. & Pelillo, M. (eds.). Berlin Heidelberg Germany: Springer, p. 183-192 10 p. (Lecture Notes in Computer Science; vol. 8621).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  11. Spherical and hyperbolic embeddings of data

    Wilson, RC., Hancock, E., Pekalska, E. & Duin, RPW., 2014, In : IEEE Transactions on Pattern Analysis and Machine Intelligence. 36, 11, p. 2255-2269 15 p.

    Research output: Contribution to journalArticleScientificpeer-review

  12. Towards scalable prototype selection by genetic algorithms with fast criteria

    Plasencia Calana, Y., Orozco Alzate, M., Mendez-Vasquez, H., García-Reyes, EB. & Duin, RPW., 2014, Proceedings of the Joint IAPR International Workshop, S+SSPR 2014. Fränti, P., Brown, G., Loog, M., Escolano, F. & Peilllo, M. (eds.). Berlin Heidelberg, Germany: Springer, p. 343-352 10 p. (Lecture Notes in Computer Science; vol. 8621).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  13. 2013
  14. FiDOS: A generalized Fisher based feature extraction method for domain shift

    Dinh, VC., Duin, RPW., Piqueras-Salazar, I. & Loog, M., 2013, In : Pattern Recognition. 46, 9, p. 2510-2518 9 p.

    Research output: Contribution to journalArticleScientificpeer-review

  15. Improving hyperspectral pixel classification with unsupervised training data selection

    Rajadell Rojas, O., Garcia-Sevilla, P., Dinh, VC. & Duin, RPW., 2013, In : IEEE Geoscience and Remote Sensing Letters. 11, 3, p. 656-660 5 p.

    Research output: Contribution to journalArticleScientificpeer-review

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