This paper presents an efficient compression-oriented segmentation algorithm for computer-generated document images. In this algorithm, a document image is represented in a block-...
A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
In this paper, we present the Gauss-Newton method as a unified approach to optimizing non-linear noise compensation models, such as vector Taylor series (VTS), data-driven parall...
We propose a new model for image denoising which is a hybrid of the total variation model and the Laplacian mean-curvature model. An efficient numerical procedure to compute the h...
In this paper, we present an innovative methodology to estimate and improve the quality of analog and mixed-signal circuit testing. We first detect and reduce the redundancy in th...
Carlo Guardiani, Patrick McNamara, Lidia Daldoss, ...