Spatiotemporal fusion in remote sensing plays an important role Earth science applications by using information complementarity between different data to improve image performance. However, several problems still exist, such as edge contour blurring and uneven pixels the predicted real ground image, extraction of salient features convolutional neural networks (CNNs). We propose a spatiotemporal...

The purpose of this study was to introduce an improved tool for automated classification of event-related potentials (ERPs) using spatiotemporally parcellated events incorporated into a functional brain network activation (BNA) analysis. The auditory oddball ERP paradigm was selected to demonstrate and evaluate the improved tool. Methods: The ERPs of each subject were decomposed into major dyna...

This paper describes a method for recognizing and measuring the motion of each individual leukocyte in microvessels from a sequence of images. A spatiotemporal image is generated whose spatial axes are parallel and vertical to vessel region contours. In order to enhance and extract only leukocyte traces with a tuned velocity range even under noisy background, we use a combination of a ltering p...

We present a method to accelerate global illumination computation in dynamic environments by taking advantage of limitations of the human visual system. A model of visual attention is used to locate regions of interest in a scene and to modulate spatiotemporal sensitivity. The method is applied in the form of a spatiotemporal error tolerance map. Perceptual acceleration combined with good sampl...

People would employ intuitive spatial relations such as ‘at’, ‘around’, ‘along’, etc. rather than the rigid global coordinates provided by GPS when they refer to physical locations in their casual communication. These word concepts, however, are considered to reflect human cognitive propensities toward the external world. Therefore they can be subjective to each human individual but as well can...

In this paper we outline how to translate verbal subjective descriptions of spatial relations into metrically meaningful positional information, and extend this capability to spatiotemporal monitoring. Document collections, transcriptions, cables, and narratives routinely make reference to objects moving through space over time. Integrating such information derived from textual sources into a g...

Purpose: Many spatiotemporal models based on image intensity have been used to accelerate cardiac image acquisition [1,2]. Their performance is limited by the fact that the local pixel intensity can abruptly change due to cardiac motion, and particularly the motion of tissue boundaries. In this work, we consider spatiotemporal models based on 2D deformation and propose an approach for simultane...

A major open problem in systems neuroscience is to understand the relationship between behavior and the detailed spiking properties of neural populations. We assess how faithfully velocity information can be decoded from a population of spiking model retinal neurons whose spatiotemporal receptive fields and ensemble spike train dynamics are closely matched to real data. We describe how to compu...