Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
In recent work, we presented a framework for many-to-many matching of multi-scale feature hierarchies, in which features and their relations were captured in a vertex-labeled, edge...
M. Fatih Demirci, Ali Shokoufandeh, Sven J. Dickin...
2. Character Recognition System The paper is about the problem of finding good prototypes for a condensed nearest neighbor classifiei- in a recognition system. A comparison study ...
General dissimilarity-based learning approaches have been proposed for dissimilarity data sets [11, 10]. They arise in problems in which direct comparisons of objects are made, e....
Service robots will have to accomplish more and more complex, open-ended tasks and regularly acquire new skills. In this work, we propose a new approach to generating plans for su...