A maximum entropy approach to natural language processing
Computational Linguistics
Maximum Entropy and Gaussian Models for Image Object Recognition
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Local Context in Non-Linear Deformation Models for Handwritten Character Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Discriminative Training for Object Recognition Using Image Patches
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A Maximum Entropy Framework for Part-Based Texture and Object Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Maximum entropy models for named entity recognition
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Sparse patch-histograms for object classification in cluttered images
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
The CLEF 2005 cross–language image retrieval track
CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories
FIRE in ImageCLEF 2005: combining content-based image retrieval with textual information retrieval
CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories
Overview of the ImageCLEF 2006 photographic retrieval and object annotation tasks
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
Features for image retrieval: an experimental comparison
Information Retrieval
Content-based video copy detection
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Combining CBIR and NLP for multilingual terminology alignment and cross-language image indexing
YIWCALA '10 Proceedings of the NAACL HLT 2010 Young Investigators Workshop on Computational Approaches to Languages of the Americas
Automatic weight selection for multi-metric distances
Proceedings of the Fourth International Conference on SImilarity Search and APplications
Retrieval of high-dimensional visual data: current state, trends and challenges ahead
Multimedia Tools and Applications
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We present and discuss our participation in the four tasks of the ImageCLEF 2006 Evaluation. In particular, we present a novel approach to learn feature weights in our content-based image retrieval system FIRE. Given a set of training images with known relevance among each other, the retrieval task is reformulated as a classification task and then the weights to combine a set of features are trained discriminatively using the maximum entropy framework. Experimental results for the medical retrieval task show large improvements over heuristically chosen weights. Furthermore the maximum entropy approach is used for the automatic image annotation tasks in combination with a part-based object model. Using our object classification methods, we obtained the best results in the medical and in the object annotation task.