Name
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 combined 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. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-642-04447-2_88 | CLEF |
Keywords | Field | DocType |
imageclefmed annotation task,feature concatenation,medical image annotation,svm confidence-based approach,populated class,multi-cue kernel,feature vector,virtual example,integration strategy,confidence-based opinion fusion,opinion maker,different combination | Computer science,Local binary patterns,Image retrieval,Concatenation,Artificial intelligence,Natural language processing,Feature vector,Automatic image annotation,Annotation,Ranking,Information retrieval,Support vector machine,Machine learning | Conference |
Volume | ISSN | ISBN |
5706 | 0302-9743 | 3-642-04446-8 |
Citations | PageRank | References |
7 | 0.63 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tatiana Tommasi | 1 | 502 | 29.31 |
| Francesco Orabona | 2 | 881 | 51.44 |
| Barbara Caputo | 3 | 3298 | 201.26 |