Kernel techniques have long been used in SVM to handle linearly inseparable problems by transforming data to a high dimensional space, but training and testing large data sets is ...
Data sets in astronomy are growing to enormous sizes. Modern astronomical surveys provide not only image data but also catalogues of millions of objects (stars, galaxies), each ob...
Bilkis J. Ferdosi, Hugo Buddelmeijer, Scott Trager...
Nonlinear registration is mostly performed after initialization by a global, linear transformation (in this work, we focus on similarity transformations), computed by a linear reg...
Darko Zikic, Michael Sass Hansen, Ben Glocker, Ali...
: se the concept of visualizing general abstract data by intermediate projection into the hyperbolic space. Its favorable properties were reported earlier and led to the "hype...
In a variety of applications (including automatic target recognition) image classification algorithms operate on compressed image data. This paper explores the design of optimal t...