Objective evaluation of segmentation quality using spatio-temporal context

Context-aware Modeling for Spatio-temporal Data Transmitted from a Wireless Body Sensor Network

Context-aware systems must be interoperable and work across different platforms at any time and in any place. Context data collected from wireless body area networks (WBAN) may be heterogeneous and imperfect, which makes their design and implementation difficult. In this research, we introduce a model which takes the dynamic nature of a context-aware system into consideration. This model is con...

Zoning of Bamdej Wetland Water Quality based on the Spatio-temporal Kriging

Inland wetlands are of the most important natural terrestrial types of water resources. Against its importance in protecting and improving biodiversity, air quality and macro-climatic condition of their regions, industrial development, and urbanization treat their natural existence and behavior. Therefore, monitoring and quality evaluation of wetlands are necessary to analyze and infer their na...

Evaluation of Tests for Separability and Symmetry of Spatio-temporal Covariance Function

In recent years, some investigations have been carried out to examine the assumptions like stationarity, symmetry and separability of spatio-temporal covariance function which would considerably simplify fitting a valid covariance model to the data by parametric and nonparametric methods. In this article, assuming a Gaussian random field, we consider the likelihood ratio separability test, a va...

Assessment of spatio-temporal variations of surface water quality and prioritization of pollution Sources (case Study: Talar Watershed, Mazandaran province)

Layered Spatio-temporal Forests for Left Ventricle Segmentation from 4D Cardiac MRI Data

In this paper we present a new method for fully automatic left ventricle segmentation from 4D cardiac MR datasets. To deal with the diverse dataset, we propose a fully automatic machine learning approach using two layers of spatio-temporal decision forests with almost no assumptions on the data or segmentation problem. We introduce 3D spatio-temporal features to classi cation with decision fore...