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Image processing of multiphase images obtained via X‐ray microtomography: a review
Easier access to X‐ray microtomography (μCT) facilities has provided much new insight
from high‐resolution imaging for various problems in porous media research. Pore space …
from high‐resolution imaging for various problems in porous media research. Pore space …
An object-based convolutional neural network (OCNN) for urban land use classification
Urban land use information is essential for a variety of urban-related applications such as
urban planning and regional administration. The extraction of urban land use from very fine …
urban planning and regional administration. The extraction of urban land use from very fine …
Ss antman je marsden l. sirovich
JKHPHJ Keener, JKBJMA Mielke, CSPKR Sreenivasan - 2005 - Springer
The main purpose of this chapter is to give a derivation, which is mathematically precise,
physically natural, and conceptually simple, of the quasilinear system of partial differential …
physically natural, and conceptually simple, of the quasilinear system of partial differential …
[Књига][B] Mathematical problems in image processing: partial differential equations and the calculus of variations
G Aubert, P Kornprobst - 2006 - Springer
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus
of Variations | SpringerLink Skip to main content Advertisement Springer Nature Link Account …
of Variations | SpringerLink Skip to main content Advertisement Springer Nature Link Account …
Segmentation of X‐ray computed tomography images of porous materials: A crucial step for characterization and quantitative analysis of pore structures
P Iassonov, T Gebrenegus… - Water resources research, 2009 - Wiley Online Library
Nondestructive imaging methods such as X‐ray computed tomography (CT) yield high‐
resolution, three‐dimensional representations of pore space and fluid distribution within …
resolution, three‐dimensional representations of pore space and fluid distribution within …
A Markov random field image segmentation model for color textured images
Z Kato, TC Pong - Image and Vision Computing, 2006 - Elsevier
We propose a Markov random field (MRF) image segmentation model, which aims at
combining color and texture features. The theoretical framework relies on Bayesian …
combining color and texture features. The theoretical framework relies on Bayesian …
3D numerical reconstruction of well-connected porous structure of rock using fractal algorithms
Natural rock, such as sandstone, has a large number of discontinuous, multi-scale, geometry-
irregular pores, forming a complex porous structure. This porous structure essentially …
irregular pores, forming a complex porous structure. This porous structure essentially …
Techniques in helical scanning, dynamic imaging and image segmentation for improved quantitative analysis with X-ray micro-CT
This paper reports on recent advances at the micro-computed tomography facility at the
Australian National University. Since 2000 this facility has been a significant centre for …
Australian National University. Since 2000 this facility has been a significant centre for …
A level set model for image classification
We present a supervised classification model based on a variational approach. This model
is devoted to find an optimal partition composed of homogeneous classes with regular …
is devoted to find an optimal partition composed of homogeneous classes with regular …
Segmentation of X‐ray CT data of porous materials: A review of global and locally adaptive algorithms
Recent computational and technological advances in X‐ray computed tomography (CT)
provide exciting new means for nondestructive, three‐dimensional imaging of soil–water …
provide exciting new means for nondestructive, three‐dimensional imaging of soil–water …