In this paper, we propose a novel approach for learning generic visual vocabulary. We use diffusion maps to au-tomatically learn a semantic visual vocabulary from ab-undant quantiz...
Jingen Liu (University of Central Florida), Yang Y...
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
Since performance on FPGAs is dominated by the routing architecture rather than wirelength, we propose a new architecture-aware approach to initial FPGA placement that models the ...
Padmini Gopalakrishnan, Xin Li, Lawrence T. Pilegg...
As an alternative to vector representations, a recent trend in image classification suggests to integrate additional structural information in the description of images in order to...
We pose the recognition problem as data association. In this setting, a novel object is explained solely in terms of a small set of exemplar objects to which it is visually simila...