Pervasive eLearning requires a novel media perspective on learning objects. Instead of viewing handhelds or smart phones as minimized PCs we would like to propose a perspective on...
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
A fast simulatedannealingalgorithmis developed for automatic object recognition. The object recognition problem is addressed as the problem of best describing a match between a hy...
Nowadays, object recognition is widely studied under the paradigm of matching local features. This work describes a genetic programming methodology that synthesizes mathematical e...
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...