International Journal of Computer Vision
Using semantic contents and WordNet in image retrieval
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
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
Negotiating the Semantic Gap: From Feature Maps to Semantic Landscapes
SOFSEM '01 Proceedings of the 28th Conference on Current Trends in Theory and Practice of Informatics Piestany: Theory and Practice of Informatics
Technical Symbols Recognition Using the Two-Dimensional Radon Transform
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
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
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The Journal of Machine Learning Research
An effective approach to document retrieval via utilizing WordNet and recognizing phrases
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Combining Visual Features with Semantics for a More Effective Image Retrieval
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Effective automatic image annotation via a coherent language model and active learning
Proceedings of the 12th annual ACM international conference on Multimedia
Using One-Class and Two-Class SVMs for Multiclass Image Annotation
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
Image annotations by combining multiple evidence & wordNet
Proceedings of the 13th annual ACM international conference on Multimedia
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Image annotation refinement using random walk with restarts
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Visual Communication and Image Representation
Information-theoretic semantic multimedia indexing
Proceedings of the 6th ACM international conference on Image and video retrieval
Bipartite graph reinforcement model for web image annotation
Proceedings of the 15th international conference on Multimedia
Personal content management system: A semantic approach
Journal of Visual Communication and Image Representation
Semantic analysis of real-world images using support vector machine
Expert Systems with Applications: An International Journal
A unified image retrieval framework on local visual and semantic concept-based feature spaces
Journal of Visual Communication and Image Representation
Automatic extraction of semantic relationships from images using ontologies and SVM classifiers
MCAM'07 Proceedings of the 2007 international conference on Multimedia content analysis and mining
A comparative study of diversity methods for hybrid text and image retrieval approaches
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Multiple Bernoulli relevance models for image and video annotation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
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In this paper, we propose a probabilistic graphical model to represent weakly annotated images. We consider an image as weakly annotated if the number of keywords defined for it is less than the maximum number defined in the ground truth. This model is used to classify images and automatically extend existing annotations to new images by taking into account semantic relations between keywords. The proposed method has been evaluated in visual-textual classification and automatic annotation of images. The visual-textual classification is performed by using both visual and textual information. The experimental results, obtained from a database of more than 30,000 images, show an improvement by 50.5% in terms of recognition rate against only visual information classification. Taking into account semantic relations between keywords improves the recognition rate by 10.5%. Moreover, the proposed model can be used to extend existing annotations to weakly annotated images, by computing distributions of missing keywords. Semantic relations improve the mean rate of good annotations by 6.9%. Finally, the proposed method is competitive with a state-of-art model.