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Poster Papers

Track: Semantic Web

Paper Title:
Image Annotation by Hierarchical Mapping of Features


In this paper, we propose a novel approach of image annotation by constructing a hierarchical mapping between low-level visual features and text features utilizing the relations within and across both visual features and text features. Moreover, we propose a novel annotation strategy that maximizes both the accuracy and the diversity of the generated annotation by generalizing or specifying the annotation in the corresponding annotation hierarchy. Experiments with 4500 scientific images from Royal Society of Chemistry journals show that the proposed annotation approach produces satisfactory results at different levels of annotations.

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