A novel nonlinear scale space framework is proposed for the purpose of multiscale image representation. The scale space decomposition problem is formulated as a general Bayesian l...
Akshaya Kumar Mishra, Alexander Wong, David A. Cla...
We are motivated by a recently developed nonlinear inverse scale space method for image denoising [5, 6], whereby noise can be removed with minimal degradation. The additive noise ...
Inspired by a broader perspective viewing intelligent system dynamics in terms of the geometry of “cognitive spaces,” we conduct a preliminary investigation of the application ...
In order to overcome the computation and storage problem for large-scale data set, an efficient iterative method of Generalized Discriminant Analysis is proposed. Because sample v...
To handle problems created by large data sets, we propose a method that uses a decision tree to decompose a given data space and train SVMs on the decomposed regions. Although the...
Fu Chang, Chien-Yang Guo, Xiao-Rong Lin, Chi-Jen L...