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Spatial Interpolants [article]

Aws Albarghouthi, Josh Berdine, Byron Cook, Zachary Kincaid
2015 arXiv   pre-print
Using the novel notion of spatial interpolants modulo theories, Splinter can infer complex invariants over general recursive predicates, e.g., of the form all elements in a linked list are even or a binary  ...  so that our technique immediately benefits from any future advances in SMT solving and interpolation.  ...  Spatial interpolants for a single command are defined as: Definition 2 (Spatial interpolant).  ... 
arXiv:1501.04100v1 fatcat:zkbago6jmnahbixu5bqcprr3c4

Spatial Interpolants [chapter]

Aws Albargouthi, Josh Berdine, Byron Cook, Zachary Kincaid
2015 Lecture Notes in Computer Science  
Using the novel notion of spatial interpolants modulo theories, SplInter can infer complex invariants over general recursive predicates, e.g., of the form all elements in a linked list are even or a binary  ...  so that our technique immediately benefits from any future advances in SMT solving and interpolation.  ...  Spatial interpolants for a single command are defined as: Definition 2 (Spatial interpolant).  ... 
doi:10.1007/978-3-662-46669-8_26 fatcat:igaxfz3slvbdtbv3odp57drxke

PMC10 SPATIAL INTERPOLATION

A Van der Steen, B Heeg, F De Charro, BA Van Hout
2007 Value in Health  
Here, two meta-modelling approaches are compared: spatial interpolation (SI) and ordinary least squares (OLS).  ...  PMC10 SPATIAL INTERPOLATION Van der Steen A, Heeg B, De Charro F,Van Hout BA Pharmerit Europe, Rotterdam, The Netherlands OBJECTIVES: The Expected Value of Perfect Parameter Information (EVPPI) requires  ... 
doi:10.1016/s1098-3015(10)65564-7 fatcat:jgxdwxs5lbg5neaxdvv4osrwgq

SPATIAL DATA INTERPOLATION

Prof.RAE ZH Aliyev
2018 International Journal of Medical and Biomedical Studies  
However, the characteristic feature of the method of inverse distance is the fact that the interpolated value in measured point is equal to the measured value.  ...  During the study and adjustment, techniques revealed our analysis of spatial data in vector format. The latter is best suited for the spatial analysis of discrete objects.  ...  This process is called interpolation of spatial data. There are many methods of interpolation data. Below are selected methods that are available in AreGIS.  ... 
doi:10.32553/ijmbs.v2i4.36 fatcat:ycomrwjqijd2doigpgyzddsgxq

Spatial interpolation: an overview

Donald E. Myers
1994 Geoderma  
The interpolation of spatial data has been considered in many different forms.  ...  One of the distinctions between kriging and other interpolators is the incorporation of the support of the samples and explicit estimation of linear functionals such as spatial integrals. that the values  ...  In general one should draw a distinction between interpolating spatial data and contouring spatial data although software packages that contour data usually provide an interpolation scheme.  ... 
doi:10.1016/0016-7061(94)90025-6 fatcat:5riwtighnnacfp4jem4on5jsgi

Interpolation of Spatial Data

Rae Zh Aliyev
2018 Biomedical Journal of Scientific & Technical Research  
However, the characteristic feature of the inverse distance method is the fact that the interpolated value at the measured point is equal to the measured value.  ...  In the course of the study, we have disclosed methods for correcting and analyzing spatial data recorded in a vector format. The latter is best suited for spatial analysis of discrete objects.  ...  Distribution of the Values of a Given Parameter Interpolation of spatial data in the ArcMap program is possible thanks to the application Spatial Analyst.  ... 
doi:10.26717/bjstr.2018.09.001746 fatcat:kfkgqweoobfeboskr63yrx437m

Random Forest Spatial Interpolation

Aleksandar Sekulić, Milan Kilibarda, Gerard B.M. Heuvelink, Mladen Nikolić, Branislav Bajat
2020 Remote Sensing  
For many decades, kriging and deterministic interpolation techniques, such as inverse distance weighting and nearest neighbour interpolation, have been the most popular spatial interpolation techniques  ...  More recently, machine learning techniques, such as random forest and gradient boosting, have become increasingly popular and are now often used for spatial interpolation.  ...  Forest Spatial Interpolation.  ... 
doi:10.3390/rs12101687 fatcat:7rm46kmex5gr7kaj6yrdy23q7e

Extrapolating and Interpolating Spatial Patterns [chapter]

M van Lieshout, A Baddeley
2002 Spatial Cluster Modelling  
Extrapolation or interpolation of a spatial pattern entails tting a stochastic model to the observed data, and computing properties of the conditional distribution of this model given the observed data  ...  Subsequently, we shall focus on the problem of identifying clusters in a spatial point pattern, which can be regarded as interpolation of a two-type point pattern from observations of points of one type  ... 
doi:10.1201/9781420035414.ch4 fatcat:hyzukvnc6jaxpiei2flifvrdda

Spatial Interpolation Using Multiple Regression

Orlando Ohashi, Luis Torgo
2012 2012 IEEE 12th International Conference on Data Mining  
Spatial imputation/interpolation methods try to fill in these unknown values in geo-referenced data sets.  ...  In this paper we evaluate our general methodology for spatial interpolation on this type of problems. Namely, we check the ability of our method to fill in unknown pixels on several images.  ...  SPATIAL INTERPOLATION -AN OVERVIEW OF THE STATE OF THE ART Forecasting the missing values in spatial data sets is not a new problem and it is usually known as spatial imputation or interpolation.  ... 
doi:10.1109/icdm.2012.48 dblp:conf/icdm/OhashiT12 fatcat:rpqyoxacufaapdjanr5s7ibgye

Spatial Interpolation of Extreme Values [article]

B. D. Youngman
2012 arXiv   pre-print
This paper introduces a method for spatial interpolation of extreme values, and in particular targets the case in which conventional data, resulting from a measurement for example, are available at only  ...  For the extreme rainfall application we find that the model estimates a variety of extremal features of interest well, and then show how specific features can be interpolated based on the model so that  ...  Spatial interpolation model formulation The model to be used for spatial interpolation is based on the hierarchical spatial model introduced in §2.2, and is outlined having assumed that a form for g()  ... 
arXiv:1203.2343v1 fatcat:mikjxwvft5ewra5cjs2xvr4zau

Spatially Adaptive Inference with Stochastic Feature Sampling and Interpolation [article]

Zhenda Xie, Zheng Zhang, Xizhou Zhu, Gao Huang, Stephen Lin
2020 arXiv   pre-print
With this sampling-interpolation scheme, our network avoids expending computation on spatial locations that can be effectively interpolated, while being robust to activation prediction errors through broadly  ...  In the feature maps of CNNs, there commonly exists considerable spatial redundancy that leads to much repetitive processing.  ...  We present a stochastic sampling and interpolation scheme to avoid expensive computation at spatial locations that can be effectively interpolated.  ... 
arXiv:2003.08866v4 fatcat:k26aymy4jrctro3yvw2xd7yaim

Spatial Morphing Kernel Regression For Feature Interpolation [article]

Xueqing Deng, Yi Zhu, Shawn Newsam
2018 arXiv   pre-print
Further, we show how prior knowledge about region boundaries can be used to improve the interpolation through spatial morphing kernel regression.  ...  We therefore investigate the problem of spatially interpolating the high-dimensional features extracted from sparse social media to enable dense labeling using standard classifiers.  ...  SMSK and SMMK outperform the interpolation methods that do not incorporate prior spatial knowledge.  ... 
arXiv:1802.07452v2 fatcat:3jm65gv3dzaadbpyejn7n5wwsy

Evaluation and comparison of spatial interpolators

Dennis Weber, Evan Englund
1992 Mathematical Geology  
EXPERIMENTAL PROCEDURE Fifteen spatial estimation methods were used in this study.  ...  The present study evaluates the relative accuracy of 15 different spatial estimators by using the same 54 sample subsets.  ... 
doi:10.1007/bf00891270 fatcat:rkhxneqkpjellfpa7nldms5os4

Spatial interpolation algorithm for error concealment

Hamid Gharavi, Shaoshuai Gao
2008 Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing  
In this paper, we propose a new spatial interpolation algorithm for Intra-Frame error concealment. The method aims at interpolating areas in the image, which have been affected by packet loss.  ...  We have proposed an edge detection technique to aid the bilinear interpolation.  ...  It takes advantage of the spatial and/or temporal correlation in the received video to interpolate the missing data.  ... 
doi:10.1109/icassp.2008.4517819 dblp:conf/icassp/GharaviG08 fatcat:5vxa5qzevzc6zjtidziewconai

EIGENVECTOR SPATIAL FILTERING BASED AREAL INTERPOLATION

Daisuke MURAKAMI, Morito TSUTSUMI
2012 Journal of Japan Society of Civil Engineers Ser D3 (Infrastructure Planning and Management)  
. : Spatial interpolation methods: A review, American Cartographer, Vol. 10, pp. 129 149, 1983. 3) Wright, J.  ...  RMSE [ SFilter] [ GWR SFilter] [ Non Spatial] 2 RMSE [ Non Spatial] RMSE 0. 4 5 30 =100×      −       30 [ SFilter] [ Non Spatial] 6 55% 73 [  ... 
doi:10.2208/jscejipm.68.59 fatcat:jthvffvepngqlkntyusi56ltja
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