1. 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 International Publishing AG, 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/Report/Conference proceedingConference contributionScientificpeer-review

  2. A benchmark and comparison of active learning for logistic regression

    Yang, Y. & Loog, M., 2018, In : Pattern Recognition. 83, p. 401-415 15 p.

    Research output: Contribution to journalArticleScientificpeer-review

  3. A framework for optimizing measurement weight maps to minimize

    Qazi, AA., Jørgensen, DR., Lillholm, M., Loog, M., Nielsen, M. & Dam, EB., 2010, In : Medical Image Analysis. 14, 3, p. 255-264 10 p.

    Research output: Contribution to journalArticleScientificpeer-review

  4. A note on an extreme case of the generalized optimal discriminant transformation

    Loog, M., Wu, X-J., Lu, J. -P., Yang, J-Y., Wang, S-T. & Kittler, J., 2008, In : Neurocomputing. 72, p. 664-665 2 p.

    Research output: Contribution to journalArticleScientificpeer-review

  5. A novel and automatic mammographic texture resemblance marker is an independent risk factor for breast cancer

    Nielsen, M., Karemore, G., Loog, M., Raundahl, J., Karssemeijer, N., Otten, JDM., Karsdal, MA., Vachon, CM. & Christiansen, C., 2010, In : Cancer Epidemiology: the international journal of cancer epidemiology, detection and prevention. 35, 4, p. 381-387 7 p.

    Research output: Contribution to journalArticleScientificpeer-review

  6. A soft-labeled self-training approach

    Mey, A. & Loog, M., 2016, 2016 23rd International Conference on Pattern Recognition (ICPR). Piscataway, NJ: IEEE, p. 2604-2609 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  7. A study of detecting cancer tissues in multispectral endoscopy data

    Dinh, VC., Loog, M., Duin, RPW., Leitner, R. & Rajadell, O., 2011, ICT.Open 2011. Smeulders, A., Karelse, F., van der Drift, R. & Stroobandt, D. (eds.). Veldhoven, The Netherlands: STW, p. 1-6 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientific

  8. A study on semi-supervised dissimilarity representation

    Dinh, VC., Duin, RPW. & Loog, M., 2012, Proceedings of 21st International Conference on Pattern Recognition (ICPR 2012). SN (ed.). Berlin, Germany: Springer, p. 2862-2864 3 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  9. A texton-based approach for the classification of lung parenchyma in CT images

    Gangeh, MJ., Sørensen, L., Shaker, SB., Kamel, MS., Bruijne, M. D. & Loog, M., 2010, In : Lecture Notes in Computer Science. 6363, p. 595-602 8 p.

    Research output: Contribution to journalArticleScientificpeer-review

  10. A variance maximization criterion for active learning

    Yang, Y. & Loog, M., 2018, In : Pattern Recognition. 78, p. 358-370 13 p.

    Research output: Contribution to journalArticleScientificpeer-review

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