1. 2019
  2. A hierarchical approach for associating body-worn sensors to video regions in crowded mingling scenarios

    Cabrera Quiros, L. & Hung, H., 2019, (Accepted/In press) In : IEEE Transactions on Multimedia. p. 1-12 12 p.

    Research output: Contribution to journalArticleScientificpeer-review

  3. Complex conversational scene analysis using wearable sensors

    Hung, H., Gedik, E. & Cabrera Quiros, L., 2019, Multimodal Behavior Analysis in the Wild: Advances and Challenges. Alameda-Pineda, X., Ricci, E. & Sebe, N. (eds.). London: Academic Press, p. 225-246 22 p.

    Research output: Chapter in Book/Report/Conference proceedingChapterScientific

  4. Divide and Count: Generic Object Counting by Image Divisions

    Stahl, T., Pintea, S. L. & Van Gemert, J. C., 2019, In : IEEE Transactions on Image Processing. 28, 2, p. 1035-1044 10 p., 8488575.

    Research output: Contribution to journalArticleScientificpeer-review

  5. Learning an MR acquisition-invariant representation using Siamese neural networks

    Kouw, W., Loog, M., Bartels, W. & Mendrik, A., 2019, (Accepted/In press) Proceedings of the IEEE International Symposium on Biomedical Imaging. IEEE

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

  6. 2018
  7. Effects of sampling skewness of the importance-weighted risk estimator on model selection

    Kouw, W. & Loog, M., 29 Nov 2018, 2018 24th International Conference on Pattern Recognition (ICPR). 2018 ed. United States of America: IEEE, p. 1468-1473 6 p.

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

  8. Automatic analysis of human social behavior in - the - wild using multimodal streams

    Cabrera Quiros, L., 27 Sep 2018, 147 p.

    Research output: ThesisDissertation (TU Delft)Scientific

  9. 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

  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

  11. Artificial Empathic Memory: Enabling Media Technologies to Better Understand Subjective User Experience

    Dudzik, B., Hung, H., Neerincx, M. & Broekens, J., 2018, Proceedings of the 2018 Workshop on Understanding Subjective Attributes of Data, with the Focus on Evoked Emotions, EE-USAD 2018. New York, NY: Association for Computing Machinery (ACM), p. 1-8 8 p.

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

  12. Asymmetric kernel in Gaussian Processes for learning target variance

    Pintea, S. L., van Gemert, J. C. & Smeulders, A. W. M., 2018, In : Pattern Recognition Letters. 108, p. 70-77 8 p.

    Research output: Contribution to journalArticleScientificpeer-review

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