Algorithms for video quality assessment (VQA) aim to estimate the qualities of videos in a manner that agrees with human judgments of quality. Modern VQA algorithms often estimate video quality by comparing localized space-time regions or groups of frames from the reference and distorted videos, using comparisons based on visual features, statistics, and/or perceptual models. We present a VQA a...

PURPOSE Results in several studies have suggested that the visual evoked potential (VEP) amplitude can vary with stimulus duration. The purpose of this study was to determine whether acuity estimates obtained by extrapolation of the sweep VEP are altered by this adaptation effect. METHODS Sweep VEP data were obtained from 16 healthy observers under binocular viewing conditions. Data were acqu...

We prove several uniforme L1 estimates on solutions of a general class of one-dimensional parabolic systems, mainly coupled in the di¤usion term, which, in fact, can be of degenerate type. They are uniform in the sense that they don’t depend on the coe¢ cients, nor on the size of the spatial domain. The estimates concern the own solution or/and its spatial gradient. This paper extends some prev...

Large spatial datasets often represent a number of spatial point processes generated by distinct entities or classes of events. When crossed with covariates, such as discrete time buckets, this can quickly result in a data set with millions of individual density estimates. Applications that require simultaneous access to a substantial subset of these estimates become resource constrained when d...

Seven independent groups estimated the location of North American cities using both spatial and numeric response modes and a variety of perceptual and memory supports. These supports included having location markers for each city color coded by nation and identified by name, giving participants the opportunity to see and update all their estimates throughout the task, and allowing them to respo...

The stochastic frontier model with heterogeneous technical efficiency explained by exogenous variables is augmented with a sparse spatial autoregressive component for a crosssection data, and a spatial-temporal component for a panel data. An estimation procedure that takes advantage of the additivity of the model is proposed, computational advantages over simultaneous maximum likelihood estimat...

Assessing spatial model performance often presents challenges related to the choice and suitability of traditional statistical methods in capturing the true validity and dynamics of the predicted outcomes. The stochastic nature of many of our contemporary spatial models of land use change necessitate the testing and development of new and innovative methodologies in statistical spatial assessme...

E¢ cient semiparametric and parametric estimates are developed for a spatial autoregressive model, containing nonstochastic explanatory variables and innovations suspected to be non-normal. The main stress is on the case of distribution of unknown, nonparametric, form, where series nonparametric estimates of the score function are employed in adaptive estimates of parameters of interest. These ...

This paper is concerned with the computational implementation of the robust RA estimates for spatial autoregressive (AR-2D) models with three parameters. The computational behavior of the RA estimators for AR-2D models which depends on the number of parameters in the model, has been studied for those models containing at most two parameters. A simulation study is carried out to compare the rela...