%0 Journal Article %1 DasiopoulouKompatsiarisStrintzis10mtaa %A Dasiopoulou, Stamatia %A Kompatsiaris, Ioannis %A Strintzis, Michael %D 2010 %J Multimedia Tools and Applications %K v1205 springer paper ai multimedia semantic processing image recognition fuzzy analysis rules knowledge zzz.th %N 1 %P 167-194 %R 10.1007/s11042-009-0393-6 %T Investigating Fuzzy DLs-based Reasoning in Semantic Image Analysis %V 49 %X Recent advances in semantic image analysis have brought forth generic methodologies to support concept learning at large scale. The attained performance however is highly variable, reflecting effects related to similarities and variations in the visual manifestations of semantically distinct concepts, much as to the limitations issuing from considering semantics solely in the form of perceptual representations. Aiming to enhance performance and improve robustness, we investigate a fuzzy DLs-based reasoning framework, which enables the integration of scene and object classifications into a semantically consistent interpretation by capturing and utilising the underlying semantic associations. Evaluation with two sets of input classifiers, configured so as to vary with respect to the wealth of concepts' interrelations, outlines the potential of the proposed approach in the presence of semantically rich associations, while delineating the issues and challenges involved.

@article{DasiopoulouKompatsiarisStrintzis10mtaa, abstract = {Recent advances in semantic image analysis have brought forth generic methodologies to support concept learning at large scale. The attained performance however is highly variable, reflecting effects related to similarities and variations in the visual manifestations of semantically distinct concepts, much as to the limitations issuing from considering semantics solely in the form of perceptual representations. Aiming to enhance performance and improve robustness, we investigate a fuzzy {DLs-based} reasoning framework, which enables the integration of scene and object classifications into a semantically consistent interpretation by capturing and utilising the underlying semantic associations. Evaluation with two sets of input classifiers, configured so as to vary with respect to the wealth of concepts' interrelations, outlines the potential of the proposed approach in the presence of semantically rich associations, while delineating the issues and challenges involved.}, added-at = {2012-05-30T10:44:48.000+0200}, author = {Dasiopoulou, Stamatia and Kompatsiaris, Ioannis and Strintzis, Michael}, biburl = {https://www.bibsonomy.org/bibtex/25094f1e53bdbf25327ad33d3f74da7cb/flint63}, doi = {10.1007/s11042-009-0393-6}, file = {SpringerLink:2010/DasiopoulouKompatsiarisStrintzis10mtaa.pdf:PDF}, groups = {public}, interhash = {59153ed5a8489af946f3ed5bb60861fe}, intrahash = {5094f1e53bdbf25327ad33d3f74da7cb}, issn = {1380-7501}, journal = {Multimedia Tools and Applications}, keywords = {v1205 springer paper ai multimedia semantic processing image recognition fuzzy analysis rules knowledge zzz.th}, number = 1, pages = {167-194}, timestamp = {2018-04-16T12:00:46.000+0200}, title = {Investigating Fuzzy {DLs-based} Reasoning in Semantic Image Analysis}, username = {flint63}, volume = 49, year = 2010 }