Learning to Detect Objects in Images via a Sparse, Part-Based Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multimedia Reasoning with f-SHIN
SMAP '07 Proceedings of the Second International Workshop on Semantic Media Adaptation and Personalization
Fuzzy spatial relation ontology for image interpretation
Fuzzy Sets and Systems
Representing and reasoning over a taxonomy of part-whole relations
Applied Ontology - Ontological Foundations of Conceptual Modelling
Managing uncertainty and vagueness in description logics for the Semantic Web
Web Semantics: Science, Services and Agents on the World Wide Web
Autonomous development of a grounded object ontology by a learning robot
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
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The problem of grasping is widely studied in the robotics community. This project focuses on the identification of object graspable features using images and object structural information. The primary aim is the creation of a framework in which the information gathered by the vision system can be integrated with automatically generated knowledge, modelled by means of fuzzy description logics.