@inbook{946512ba5849416f9d0ac926613ecf4f,
title = "Machine Learning for Visual Concept Recognition and Ranking for Images",
abstract = "Recognition of a large set of generic visual concepts in images and ranking of images based on visual semantics is one of the unsolved tasks for future multimedia and scientific applications based on image collections. From that perspective, improvements of the quality of semantic annotations for image data are well matched to the goals of the THESEUS research program with respect to multimedia and scientific services. We will introduce the data-driven and algorithmic challenges inherent in such tasks from a perspective of statistical data analysis and machine learning and discuss approaches relying on kernel-based similarities and discriminative methods which are capable of processing large-scale datasets.",
author = "Alexander Binder and Wojciech Samek and M{\"u}ller, {Klaus Robert} and Motoaki Kawanabe",
note = "Funding Information: This work was primarily supported by the German Federal Ministry for Economic Affairs and Energy (BMWi) under the THESEUS research program (Grant 01MQ07018). Furthermore it was in part supported by the World Class University Program through the National Research Foundation of Korea funded by the Korean Ministry of Education, Science, and Technology, under Grant R31-10008. We express our thanks to Volker Tresp, the work package leader at CTC WP6, Ralf Sch{\"a}fer from the Fraunhofer HHI and Shinichi Nakajima from the Nikon corporation for the fruitful collaboration.",
year = "2014",
doi = "10.1007/978-3-319-06755-1_17",
language = "English",
isbn = "9783319067544",
series = "Cognitive Technologies",
publisher = "Springer Verlag",
pages = "211--223",
booktitle = "Towards the Internet of Services The THESEUS Research Program",
}