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={E. Chang and Kingshy Goh and Gerard Sychay and G. Wu},
  journal={IEEE Trans. Circuits Syst. Video Technol.},
  year={2003},
  volume={13},
  pages={26-38}
}
  • E. Chang, Kingshy Goh, +1 author G. Wu
  • Published 2003
  • Computer Science
  • IEEE Trans. Circuits Syst. Video Technol.
  • 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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