In stochastic thresholding, the threshold for quantization of a signal is randomized. An estimator based on quantized signal data can be optimized through stochastic thresholding. ...
This paper presents a method for estimating uncertainty in MRI-based brain region delineations provided by fully-automated segmentation methods. In large data sets, the uncertainty...
Karl R. Beutner, Gautam Prasad, Evan Fletcher, Cha...
Traditional methods for evaluating the amount of anonymity afforded by various Mix configurations have depended on either measuring the size of the set of possible senders of a p...
Richard E. Newman, Vipan R. Nalla, Ira S. Moskowit...
We describe how to teach deformable models to maximize image segmentation correctness based on user-specified criteria, and we present a method for evaluating which criteria work ...
Within Valiant'smodel of learning as formalized by Kearns, we show that computable total predicates for two formallyuncomputable problems the classical Halting Problem, and t...