Information Fusion for Combining Visual and Textual Image Retrieval

@article{Zhou2010InformationFF,
  title={Information Fusion for Combining Visual and Textual Image Retrieval},
  author={Xin Zhou and Adrien Depeursinge and Henning M{\"u}ller},
  journal={2010 20th International Conference on Pattern Recognition},
  year={2010},
  pages={1590-1593}
}
In this paper, classical approaches such as maximum combinations (combMAX), sum combinations (comb-SUM) and the product of the maximum and a non–zero number (combMNZ) were employed and the trade–off between two fusion effects (chorus and dark horse effects) was studied based on the sum of n maximums. Various normalization strategies were tried out. The fusion algorithms are evaluated using the best four visual and textual runs of the ImageCLEF medical image retrieval task 2008 and 2009. The… CONTINUE READING
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