Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
Given any collection of data cells in a data space X, consider the problem of finding the optimal partition of the data cells into blocks which are unions of cells. The algorithms...
Bradley W. Jackson, Jeffrey D. Scargle, Chris Cusa...
We describe the application of a time domain diffuse fluorescence tomography system for whole body small animal imaging. The key features of the system are the use of point excitat...
Anand T. N. Kumar, Scott B. Raymond, Andrew K. Dun...
Background: Digital atlases provide a common semantic and spatial coordinate system that can be leveraged to compare, contrast, and correlate data from disparate sources. As the q...
A new method for color reduction in a digital image is proposed, which is based on the development of a new neural network classifier and on a new method for Estimation of the Mos...