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Results: 516
Number of items: 516
  • Snoek, C. G. M., Worring, M., & Smeulders, A. W. M. (2005). Early versus Late Fusion in Semantic Video Analysis. In ACM Multimedia
  • Pham, T. V., & Smeulders, A. W. M. (2005). Object recognition with uncertain geometry and uncertain part detection. Computer Vision and Image Understanding, 99(2), 241-258. https://doi.org/10.1016/j.cviu.2005.01.006
  • Geusebroek, J. M., Burghouts, G. J., van Gemert, J. C., & Smeulders, A. W. M. (2005). Invariant representations to prepare for content based image retrieval from first principles. In R. Veltkamp (Ed.), Trends and Advances in Content-Based Image and Video Retrieval Springer-Verlag.
  • Snoek, C. G. M., van Gemert, J. C., Geusebroek, J. M., Huurnink, B., Koelma, D. C., Nguyen, G. P., de Rooij, O., Seinstra, F. J., Smeulders, A. W. M., Veenman, C. J., & Worring, M. (2005). The MediaMill trecvid 2005 semantic video engine. In Proceedings of the 3rd TRECVID Workshop (pp. 225-226). NIST.
  • Hoang, M. A., Geusebroek, J. M., & Smeulders, A. W. M. (2005). Color texture measurement and segmentation. Signal Processing, 85(2), 265-275. https://doi.org/10.1016/j.sigpro.2004.10.009
  • Open Access
    van de Weijer, J. (2005). Color features and local structure in images. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Pham, T. V. (2005). Learning spatial relations for object recognition. [Thesis, fully internal, Universiteit van Amsterdam].
  • Nguyen, T. H., & Smeulders, A. W. M. (2004). Active learning using preclustering. In Proceedings of the 21st International Conference on Machine Learning ICML04
  • Nguyen, T. H., & Smeulders, A. W. M. (2004). Everything gets better all the time apart from the amount of data. In P. Enser, Y. Kompatsiaris, N. E. O'Connor, A. F. Smeaton, & A. W. M. Smeulders (Eds.), Image and Video Retrieval - Proceedings of CIVR04 (pp. 33-41). Springer Verlag GmbH.
  • Pham, T. V., & Smeulders, A. W. M. (2004). Statistical strategy for object class recognition using part detectors. In Statistical Learning in Computer Vision
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