We present a new, sophisticated algorithm to select suitable training images for our biologically motivated attention system VOCUS. The system detects regions of interest depending...
We consider the general, widely applicable problem of selecting from n real-valued random variables a subset of size m of those with the highest means, based on as few samples as ...
We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse,...
In background subtraction, cast shadows induce silhouette distortions and object fusions hindering performance of high level algorithms in scene monitoring. We introduce a nonpara...
Abstract. Feature subset selection is an important subject when training classifiers in Machine Learning (ML) problems. Too many input features in a ML problem may lead to the so-...