We introduce a new task-independent framework to model top-down overt visual attention based on graphical models for probabilistic inference and reasoning. We describe a Dynamic B...
We address the problem of object-based visual attention from a Bayesian standpoint. We contend with the issue of joint segmentation and saliency computation suitable to provide a ...
We study the synthesis of neural coding, selective attention and perceptual decision making. We build a hierarchical neural architecture that implements Bayesian integration of no...
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Abstract— This paper presents the search problem formulated as a decision problem, where the searcher decides whether the target is present in the search region, and if so, where...