Hierarchical classification for automatic image annotation

@inproceedings{Fan2007HierarchicalCF,
  title={Hierarchical classification for automatic image annotation},
  author={Jianping Fan and Yuli Gao and Hangzai Luo},
  booktitle={SIGIR},
  year={2007}
}
In this paper, a hierarchical classification framework has been proposed for bridging the semantic gap effectively and achieving multi-level image annotation automatically. First, the semantic gap between the low-level computable visual features and users' real information needs is partitioned into four smaller gaps, and multiple approachesallare proposed to bridge these smaller gaps more effectively. To learn more reliable contextual relationships between the atomic image concepts and the co… CONTINUE READING
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Mining image databases on semantics via statistical learning

  • J. Fan, H. Luo, Y. Gao, M.-S. Hacid
  • KDD
  • 2005
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