Similarity search in image database is commonly implemented as nearest-neighbor search in a feature space of the images. For that purpose, a large number of different features as ...
This paper describes an approach (and its implementation) on how to handle the large number of data from user centered engineering processes. It uses objectoriented abstraction me...
Prediction of financial time series using artificial neural networks has been the subject of many publications, even if the predictability of financial series remains a subject of ...
Amaury Lendasse, John Aldo Lee, Eric de Bodt, Vinc...
Medical Terminological Knowledge Bases contain a large number of primitive concept definitions. This is due to the large number of natural kinds that are represented, and due to t...
: Traditional state modeling techniques have several limitations. One of these is the reduced ability to model a large number of variables simultaneously. Another limitation is tha...
Gregory Vert, Sergiu M. Dascalu, Frederick C. Harr...
A frequently encountered problem in decision making is the following review problem: review a large number of objects and select a small number of the best ones. An example is sel...
Neuroimaging datasets often have a very large number of voxels and a very small number of training cases, which means that overfitting of models for this data can become a very se...
Tanya Schmah, Geoffrey E. Hinton, Richard S. Zemel...
Data ONTAP GX is a clustered Network Attached File server composed of a number of cooperating filers. Each filer manages its own local file system, which consists of a number of d...
Michael Eisler, Peter Corbett, Michael Kazar, Dani...
Schema matching is a crucial task to gather information of the same domain. This is more true on the web, where a large number of data sources are available and require to be matc...
Currently compilers contain a large number of optimisations which are based on a set of heuristics that are not guaranteed to be effective to improve the performance metrics. In th...