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 [BibTeX] [Marc21]
An SVM Confidence-Based Approach to Medical Image Annotation
Type of publication: Conference paper
Citation: Tommasi_IMAGECLEF_2008
Booktitle: Workshop of the Cross-Language Evaluation Forum
Series: LNCS
Year: 2008
Abstract: This paper presents the algorithms and results of the “idiap” team participation to the ImageCLEFmed annotation task in 2008. On the basis of our successful experience in 2007 we decided to integrate two different local structural and textural descriptors. Cues are com- bined through concatenation of feature vectors and through the Multi- Cue Kernel. The challenge this year was to annotate images coming mainly from classes with only few training examples. We tackled the problem on two fronts: (1) we introduced a further integration strategy using SVM as an opinion maker; (2) we enriched the poorly populated classes adding virtual examples. We submitted several runs considering different combinations of the proposed techniques. The run jointly using the feature concatenation, the confidence-based opinion fusion and the virtual examples ranked first among all submissions.
Keywords:
Projects Idiap
EMMA
Authors Tommasi, Tatiana
Orabona, Francesco
Caputo, Barbara
Editors Peters, Carol
Giampiccolo, Danilo
Ferro, Nicola
Added by: [UNK]
Total mark: 0
Attachments
  • Tommasi_IMAGECLEF_2008.pdf
Notes