A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
A Bayesian framework for deformable pattern classification has been proposed in [1] with promising results for isolated handwritten character recognition. Its performance, however...
Multispectral remote sensing images are widely used for automated land use and land cover classification tasks. Remotely sensed images usually cover large geographical areas, and s...
In this paper a graph-based method is presented which not only characterizes topological classification of the tessellated surfaces but also simultaneously generates the substanti...