We propose an adaptive procedure for segmenting images by merging of homogeneous regions. The algorithm is based on sharp concentration inequalities and is tailored to avoid over-...
—With the exponential growth in the amount of data that is being generated in recent years, there is a pressing need for applying machine learning algorithms to large data sets. ...
The support-confidence framework is the most common measure used in itemset mining algorithms, for its antimonotonicity that effectively simplifies the search lattice. This com...
We address the problem of scale selection in texture analysis. Two di erent scale parameters, feature scale and statistical scale, are dened. Statistical scale is the size of the r...
With the growing use of distributed information networks, there is an increasing need for algorithmic and system solutions for data-driven knowledge acquisition using distributed,...
Doina Caragea, Jaime Reinoso, Adrian Silvescu, Vas...