Given several related learning tasks, we propose a nonparametric Bayesian model that captures task relatedness by assuming that the task parameters (i.e., predictors) share a late...
We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
—Face recognition performance depends upon the input variability as encountered during biometric data capture including occlusion and disguise. The challenge met in this paper is...
— In this paper, we present a new combination of a biologically inspired attention system (VOCUS – Visual Object detection with a CompUtational attention System) with a robust ...
Current manufacturing methods for robotic-controlled assembly rely on accurate positioning to ensure task completion, often through the use of special xtures and precise calibrati...