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The creation of golden standard datasets is a costly business. Optimally more than one judgment per document is obtained to ensure a high quality on annotations. In this context, we explore how much annotations from experts differ from each other, how different sets of annotations influence the ranking of systems and if these annotations can be obtained(More)
The ImageCLEF 2010 Photo Annotation Task poses the challenge of automated annotation of 93 visual concepts in Flickr photos. The participants were provided with a training set of 8,000 Flickr images including annotations, EXIF data and Flickr user tags. Testing was performed on 10,000 Flickr images, differentiated between approaches considering solely(More)
Multilabel classification using ontology information is an emerging research area that combines machine learning methods with knowledge models. The performance assessment of such classification systems poses new challenges. We propose an evaluation measure that considers the mapping of label sets to their groundtruth and allows for the incorporation of real(More)
The ImageCLEF 2011 Photo Annotation and Concept-based Retrieval Tasks pose the challenge of an automated annotation of Flickr images with 99 visual concepts and the retrieval of images based on query topics. The participants were provided with a training set of 8,000 images including annotations, EXIF data, and Flickr user tags. The annotation challenge was(More)
The large-scale visual concept detection and annotation task (LS-VCDT) in Image-CLEF 2009 aims at the detection of 53 concepts in consumer photos. These concepts are structured in an ontology which implies a hierarchical ordering and which can be utilized during training and classification of the photos. The dataset consists of 18.000 Flickr photos which(More)
Mood or emotion information are often used search terms or navigation properties within multimedia archives, retrieval systems or multimedia players. Most of these applications engage end-users or experts to tag multimedia objects with mood annotations. Within the scientific community different approaches for content-based music, photo or multimodal mood(More)
Supervised learning requires adequately labeled training data. In this paper, we present an approach for automatic detection of outliers in image training sets using an one-class Support Vector Machine (SVM). The image sets were down-loaded from photo communities solely based on their tags. We conducted four experiments to investigate if the one-class SVM(More)
Cine Magnetic Resonance (MR) imaging has become the method-of-choice for the examination of the dynamic behaviour of the heart. An assessment of the left ventricle can reveal regions of myocardial dysfunction and their severeness. The scope of this work is a complete analysis of the left ventricular dynamics for the usage in a clinical environment. For that(More)
With the steadily increasing amount of multimedia documents on the web and at home, the need for reliable semantic indexing methods that assign multiple keywords to a document grows. The performance of existing approaches is often measured with standard evaluation measures of the information retrieval community. In a case study on image annotation, we show(More)
  • Marc Trimborn, Mahdi Ghani, Diego J. Walther, Monika Dopatka, Véronique Dutrannoy, Andreas Busche +15 others
  • 2010
Mutations in the human gene MCPH1 cause primary microcephaly associated with a unique cellular phenotype with premature chromosome condensation (PCC) in early G2 phase and delayed decondensation post-mitosis (PCC syndrome). The gene encodes the BRCT-domain containing protein microcephalin/BRIT1. Apart from its role in the regulation of chromosome(More)