A bayesian formulation for sub-pixel refinement in stereo orbital imagery

Author(s):  
Ara V. Nefian ◽  
Kyle Husmann ◽  
Michael Broxton ◽  
Vinh To ◽  
Michael Lundy ◽  
...  
Keyword(s):  
2014 ◽  
Vol 50 (4) ◽  
pp. 521-534
Author(s):  
CALUM MILLER

AbstractThere has been a trend within natural theology to present arguments for theism deductively, such that at least one of the premises is likely to be extremely controversial. For those arguments with less controversial premises, the conclusion is usually something short of theism. On these grounds, some have employed probabilistic reasoning to revive classical arguments – to use less controversial premises in achieving a conclusion directly relevant to whether theism is true or not. Here, I formulate the kalam cosmological argument in Bayesian terms, and argue that doing so renders many objections levelled against it obsolete.


2020 ◽  
Author(s):  
Eleanor Brower Schille-Hudson ◽  
David Landy

Demographic perception—the perception of social quantities of geopolitical scale and social significance—has been extensivelystudied in cognitive and political science (Citrin & Sides, 2008; Gilens, 2001; Herda, 2013). Regular patterns of over- and under-estimation emerge. Americans greatly overestimate, for instance, the proportion of citizens that identify as gay or Muslim, while underestimating those that are Christian. While these errors have been attributed to social factors such as fear of specific minorities (Gallagher, 2003; Wong, 2007), other work has suggested that these patterns result from the psychophysics of the perception of proportions (Landy, Guay & Marghetis 2018). A Bayesian formulation suggests that biases in the estimation of both social proportions and simple visual properties result from a common source: ‘hedging’ uncertain information toward a prior. Here we present a novel lab paradigm and two experiments that manipulate uncertainty in a simple (dot estimation) task, verifying the core assumptions of the Bayesian approach.


Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4416 ◽  
Author(s):  
Defu Jiang ◽  
Ming Liu ◽  
Yiyue Gao ◽  
Yang Gao ◽  
Wei Fu ◽  
...  

The random finite set (RFS) approach provides an elegant Bayesian formulation of the multi-target tracking (MTT) problem without the requirement of explicit data association. In order to improve the performance of the RFS-based filter in radar MTT applications, this paper proposes a time-matching Bayesian filtering framework to deal with the problem caused by the diversity of target sampling times. Based on this framework, we develop a time-matching joint generalized labeled multi-Bernoulli filter and a time-matching probability hypothesis density filter. Simulations are performed by their Gaussian mixture implementations. The results show that the proposed approach can improve the accuracy of target state estimation, as well as the robustness.


Author(s):  
Ernesto Heredia-Zavoni ◽  
Antonio Zeballos ◽  
Roberto Montes-Iturrizaga ◽  
Luis Esteva

Abstract This paper discusses the estimation of probability distributions of damage using response records from instrumented buildings subjected to seismic excitations. The objective of the paper is to show how the information on the evolution of the mechanical properties of a system can be used to assess the state of cumulative damage. This implies expressing damage on the structural members in terms of its influence on the residual mechanical properties of the system. The information on the inelastic behavior from response records is used in a bayesian formulation along with a damage function to update prior probability distributions of damage. The damage function models the hysteretic cycles of inelastic response in terms of an initial damage and of the displacement amplitudes of the response cycles. It describes the evolution of the secant stiffness through the cycles of inelastic response as a function of cumulative damage and displacement amplitudes. The updating of probability distributions of damage for single degree of freedom systems is presented first. Extensions to the case of non-linear multi-degree of freedom systems are discussed next. Examples of reinforced concrete frames are given for illustrative purposes.


1994 ◽  
Vol 44 (1-2) ◽  
pp. 11-28 ◽  
Author(s):  
A. K. Basu ◽  
J. K. Das

This paper develops a Bayesian formulation of Kalman filter under the errors having elliptically contoured distributions in both observation equation and system (or state) equation, using some recent results in multivariate analysis. Estimation of parameters in case of missing observations and prediction of missing observations as well are dealt with under the above set up of autoregressive-moving average process in time series. Two illustrative examples are presented with the help of AR(1) model and ARMA (1, 1) model.


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