CBSA: content-based soft annotation for multimodal image retrieval using Bayes point machines

@article{Chang2003CBSACS,
  title={CBSA: content-based soft annotation for multimodal image retrieval using Bayes point machines},
  author={Edward Y. Chang and Kingshy Goh and Gerard Sychay and Gang Wu},
  journal={IEEE Trans. Circuits Syst. Video Techn.},
  year={2003},
  volume={13},
  pages={26-38}
}
We propose a content-based soft annotation (CBSA) procedure for providing images with semantical labels. The annotation procedure starts with labeling a small set of training images, each with one single semantical label (e.g., forest, animal, or sky). An ensemble of binary classifiers is then trained for predicting label membership for images. The trained ensemble is applied to each individual image to give the image multiple soft labels, and each label is associated with a label membership… CONTINUE READING

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