The nature of statistical learning theory
The nature of statistical learning theory
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Methods for precise named entity matching in digital collections
Proceedings of the 3rd ACM/IEEE-CS joint conference on Digital libraries
Automatic image annotation and retrieval using cross-media relevance models
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The Journal of Machine Learning Research
Understanding captions in biomedical publications
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
LabelMe: A Database and Web-Based Tool for Image Annotation
International Journal of Computer Vision
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Detailed image annotation necessary for reliable image retrieval involves not only annotating the image as a single artifact, but also annotating specific objects or regions within the image. Such detailed annotation is a costly endeavor and the available annotated image data are quite limited. This paper explores the feasibility of using image captions from scientific journals for the purpose of automatically annotating image regions. Salient image clues, such as an object location within the image or an object color, together with the associated explicit object mention, are extracted and classified using rule-based and SVM learners.