We propose a new method for handwritten word-spotting which does not require prior training or gathering examples for querying. More precisely, a model is trained "on the fly...
By mapping a set of input images to points in a lowdimensional manifold or subspace, it is possible to efficiently account for a small number of degrees of freedom. For example, i...
This paper presents algorithms for efficiently computing the covariance matrix for features that form sub-windows in a large multidimensional image. For example, several image proc...
Functional Magnetic Resonance Imaging(fMRI) has enabled scientists to look into the active human brain, leading to a flood of new data, thus encouraging the development of new data...
Lei Zhang 0002, Dimitris Samaras, Dardo Tomasi, Ne...
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...