Sampling is a popular way of scaling up machine learning algorithms to large datasets. The question often is how many samples are needed. Adaptive stopping algorithms monitor the ...
We present a novel algorithm for computing a training set consistent subset for the nearest neighbor decision rule. The algorithm, called FCNN rule, has some desirable properties....
Object detection in video surveillance is typically done through background subtraction or temporal differencing. While these techniques perform very well under scenes where there...
—DASH is a small, lightweight, power autonomous robot capable of running at speeds up to 15 body lengths per second (see video). Drawing inspiration from biomechanics, DASH has a...
Random Walks (RWs) have been considered for information dissemination in large scale, dynamic and unstructured environments, as they are scalable, robust to topology changes and d...