%Aigaion2 BibTeX export from Idiap Publications
%Saturday 20 April 2024 08:52:17 AM

         author = {Tommasi, Tatiana and Orabona, Francesco and Caputo, Barbara},
       projects = {Idiap, EMMA},
          title = {Cue Integration for Medical Image Annotation},
      booktitle = {Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers},
         series = {LNCS},
           year = {2008},
      publisher = {Springer-Verlag},
       abstract = {This paper presents the algorithms and results of our par-
ticipation to the image annotation task of ImageCLEFmed 2007. We
proposed a multi-cue approach where images are represented both by
global and local descriptors. These cues are combined following two SVM-
based strategies. The first algorithm, called Discriminative Accumulation
Scheme (DAS,',','),
 trains an SVM for each feature, and considers as output
of each classifier the distance from the separating hyperplane. The final
decision is taken on a linear combination of these distances. The second
algorithm, that we call Multi Cue Kernel (MCK,',','),
 uses a new Mercer
kernel which can accept as input different features while keeping them
separated. The DAS algorithm obtained a score of 29.9, which ranked
fifth among all submissions. The MCK algorithm with the one-vs-all
and with the one-vs-one multiclass extensions of SVM scored respec-
tively 26.85 and 27.54. These runs ranked first and second among all
            pdf = {https://publications.idiap.ch/attachments/papers/2009/Tommasi_CLEF_2008.pdf}