Compressive Sensing is an emerging field based on the revelation that a small group of non-adaptive linear projections of a compressible signal contains enough information for rec...
Michael B. Wakin, Jason N. Laska, Marco F. Duarte,...
We consider the sensor broadcast problem: in our setup, sensors measure each one pixel of an image that unfolds over a field, and broadcast a rate constrained encoding of their me...
1 A kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. In this work, we propo...
Statistical modeling for content based retrieval is examined in the context of recent TREC Video benchmark exercise. The TREC Video exercise can be viewed as a test bed for evalua...
Milind R. Naphade, Sankar Basu, John R. Smith, Chi...
In this paper we present a novel system for the detection and extraction of road map information from high-resolution satellite imagery. Uniquely, the proposed system is an integr...