Using a Gaussian scale space, one can use the extra dimension, viz. scale, for investigation of "built-in" properties of the image in scale space. We show that one of such induced properties is the nesting of special iso-intensity manifolds, which yield an implicitly present hierarchy of the critical points and regions of their influence, in the original image. Its very nature allows one not on...

I find a topological arrangement of stocks traded in a financial market which has associated a meaningful economic taxonomy. The topological space is a graph connecting the stocks of the portfolio analyzed. The graph is obtained starting from the matrix of correlation coefficient computed between all pairs of stocks of the portfolio by considering the synchronous time evolution of the differenc...

Hierarchical and recursive structure is commonly found in inputs from the richest sensory modalities, including natural language sentences and scene images. But such hierarchical structure has traditionally been a strong point of both structured and supervised models (whether symbolic of probabilistic) and a weak point of both neural networks and unsupervised learning. I will present some of ou...

Zusammenfassung In principle, stereo vision can be used to create a three-dimensional representation for the surrounding world. In practice, most stereo algorithms fail to do so securely. Schemes to overcome intrinsic problems of common stereo algorithms are investigated and new collective algorithms proposed. Possible neural implementations are discussed.

s: There are three basic multilevel structures for hierarchical models, namely, incremental, aggregated and cascaded. Designing of these hierarchical models faces many difficulties including determination of the hierarchical structure, parameter identification and input variables selection for each submodels. A tree-structure based Hierarchical Hybrid Soft Computing (HHSC) framework is presente...

Many methods for inferring genetic networks have been proposed, but the regulations they infer often include false-positives. Several researchers have attempted to reduce these erroneous regulations by proposing the use of a priori knowledge about the properties of genetic networks such as their sparseness, scale-free structure, and so on. This study focuses on another piece of a priori knowled...