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- W2295162216 abstract "This paper presents our submitted experiments in the Concept anno- tation and Concept Retrieval tasks using Flickr photos at ImageCLEF 2012. This edition we applied new strategies for both the textual and the visual sub- systems included in our multimodal retrieval system. The visual subsystem has focus on extending the low-level features vector with concept features. These concept features have been calculated by means of a logistic regression model. The textual subsystem has focus on expanding the query information using ex- ternal resources. Our best concept retrieval run, a multimodal one, is at the ninth position with a MnAP of 0.0295, being the second best group of the con- test for the multimodal modality. This is also our best run in the global ordered list (where eleven textual runs are also better than it). We have adapted our mul- timodal retrieval process for the annotation task obtaining non-very good results for this first participation, with a MiAP of 0.1020." @default.
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- W2295162216 date "2012-01-01" @default.
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- W2295162216 title "Visual Concept Features and Textual Expansion in a Multimodal System for Concept Annotation and Retrieval with Flickr Photos at ImageCLEF2012" @default.
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