We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse,...
Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...
In region machining, neighbouring regions may be close together, but disconnected. Boundary curves may also have unwanted geometric artifacts caused by approximation and discretis...
A basic problem in the management of web servers is capacity planning: you want enough capacity to be able to serve peak loads, but not too much so as to avoid excessive costs. It...
This work exploits several machine-learning techniques to address the problem of image-quality prediction of synthetic aperture sonar (SAS) imagery. The objective is to predict th...