This paper presents a novel approach for detection and segmentation of generic shapes in cluttered images. The underlying assumption is that generic objects that are man made, fre...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
In supervised learning, a training set consisting of labeled instances is used by a learning algorithm for generating a model (classifier) that is subsequently employed for decidi...
We propose a new definition of the representation theorem for many-valued logics, with modal operators as well, and define the stronger relationship between algebraic models of ...
The ever-growing choice in diverse services is making service orchestration variability an essential aspect of a composite web service. Influence of this variation on the Quality o...
Ajay Kattepur, Sagar Sen, Benoit Baudry, Albert Be...