Automatic generation of semantic metadata describing spatial relations is highly desirable for image digital libraries. Relative spatial relations between objects in an image conv...
Yuhang Wang, Fillia Makedon, James Ford, Li Shen, ...
In this paper, we propose an autonomous learning scheme to automatically build visual semantic concept models from the output data of Internet search engines without any manual la...
In content-based image retrieval, relevance feedback has been introduced to narrow the gap between low-level image feature and high-level semantic concept. Furthermore, to speed u...
In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Given a query image, MRBIR first makes use of a manifold ra...
“The Multi-User Programming Pedagogy for Enhancing Traditional Study” (MUPPETS) system has been under development at RIT for the last three years. This multi-user environment ...