Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Retrieval Using Multiple Evidence Ranking
IEEE Transactions on Knowledge and Data Engineering
A Probabilistic Semantic Model for Image Annotation and Multi-Modal Image Retrieva
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
ChemXSeer: a digital library and data repository for chemical kinetics
Proceedings of the ACM first workshop on CyberInfrastructure: information management in eScience
Investigating visual feature extraction methods for image annotation
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
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In this paper, we propose a novel approach of image annotation byconstructing a hierarchical mapping between low-level visualfeatures and text features utilizing the relations within and acrossboth visual features and text features. Moreover, we propose a novelannotation strategy that maximizes both the accuracy and thediversity of the generated annotation by generalizing or specifyingthe annotation in the corresponding annotation hierarchy.Experiments with 4500 scientific images from Royal Society ofChemistry journals show that the proposed annotation approachproduces satisfactory results at different levels of annotations.