In this work we take a novel view of nonlinear manifold learning. Usually, manifold learning is formulated in terms of finding an embedding or `unrolling' of a manifold into ...
We introduce the problem of repetitive nearest neighbor search in relevance feedback and propose an efficient search scheme for high dimensional feature spaces. Relevance feedback...
In this paper, we introduce the concept of hierarchy-based fault-local stabilization and a novel self-healing/fault-containment technique and apply them in Stalk. Stalk is an algo...
Murat Demirbas, Anish Arora, Tina Nolte, Nancy A. ...
Location information is very useful in the design of sensor network infrastructures. In this paper, we study the anchor-free 2D localization problem by using local angle measureme...
We study in this paper the problem of bridging the semantic gap between low-level image features and high-level semantic concepts, which is the key hindrance in content-based imag...