A logical framework for depiction and image interpretation
Artificial Intelligence
ERNEST: A Semantic Network System for Pattern Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Knowledge-based image understanding systems: a survey
Computer Vision and Image Understanding
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Possibility Theory, Probability Theory and Multiple-Valued Logics: A Clarification
Annals of Mathematics and Artificial Intelligence
Semantic Annotation of Sports Videos
IEEE MultiMedia
Knowledge Representation and Control in Computer Vision Systems
IEEE Expert: Intelligent Systems and Their Applications
Towards Computer Vision with Description Logics: Some Recent Progress
SPELMG '99 Proceedings of the Integration of Speech and Image Understanding
Extensions to description logics
The description logic handbook
Machine Learning
Evaluation campaigns and TRECVid
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
The challenge problem for automated detection of 101 semantic concepts in multimedia
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
How many high-level concepts will fill the semantic gap in news video retrieval?
Proceedings of the 6th ACM international conference on Image and video retrieval
Semantic annotation and retrieval of video events using multimedia ontologies
ICSC '07 Proceedings of the International Conference on Semantic Computing
On scene interpretation with description logics
Image and Vision Computing
Multimedia Reasoning with f-SHIN
SMAP '07 Proceedings of the Second International Workshop on Semantic Media Adaptation and Personalization
Realizing the Hydrogen Economy through Semantic Web Technologies
IEEE Intelligent Systems
Reasoning within fuzzy description logics
Journal of Artificial Intelligence Research
Reasoning with very expressive fuzzy description logics
Journal of Artificial Intelligence Research
A self-referential perceptual inference framework for video interpretation
ICVS'03 Proceedings of the 3rd international conference on Computer vision systems
Approaches to inconsistency handling in description-logic based ontologies
OTM'07 Proceedings of the 2007 OTM Confederated international conference on On the move to meaningful internet systems - Volume Part II
A fine-grained approach to resolving unsatisfiable ontologies
Journal on data semantics X
A framework for handling inconsistency in changing ontologies
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Repairing unsatisfiable concepts in OWL ontologies
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
A probabilistic framework for semantic video indexing, filtering,and retrieval
IEEE Transactions on Multimedia
Adding Semantics to Detectors for Video Retrieval
IEEE Transactions on Multimedia
Learning Midlevel Image Features for Natural Scene and Texture Classification
IEEE Transactions on Circuits and Systems for Video Technology
Extracting semantics from audio-visual content: the final frontier in multimedia retrieval
IEEE Transactions on Neural Networks
Semantic representation of multimedia content
Knowledge-driven multimedia information extraction and ontology evolution
A reward-and-punishment-based approach for concept detection using adaptive ontology rules
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Aggregation operators for fuzzy ontologies
Applied Soft Computing
MOWL: An ontology representation language for web-based multimedia applications
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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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.