scholarly journals Unsupervised image segementation by stochastic reconstruction

1998 ◽  
Author(s):  
Volker H. Metzler ◽  
Ralf Vandenhouten ◽  
Joerg Krone ◽  
Reinhard Grebe
Keyword(s):  
Stochastic Reconstruction ◽  
Image Segementation

A hybrid process-based and stochastic reconstruction method of porous media

2008 ◽  
Vol 110 (1) ◽  
pp. 92-99 ◽  
Author(s):  
M.G. Politis ◽  
E.S. Kikkinides ◽  
M.E. Kainourgiakis ◽  
A.K. Stubos
Keyword(s):  
Porous Media ◽  
Hybrid Process ◽  
Reconstruction Method ◽  
Stochastic Reconstruction

Stochastic Reconstruction of Complex Heavy Oil Molecules Using an Artificial Neural Network

2017 ◽  
Vol 31 (11) ◽  
pp. 11932-11938 ◽  
Author(s):  
Celal Utku Deniz ◽  
Muzaffer Yasar ◽  
Michael T. Klein
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Heavy Oil ◽  
Stochastic Reconstruction ◽  
Artificial Neural

scholarly journals An Improved Dual Clustering Method for Classification of Microarray Image Segementation

2019 ◽  
Vol 8 (4) ◽  
pp. 2514-2519
Keyword(s):  
Support Vector Machine ◽  
Ct Scanning ◽  
Support Vector ◽  
Nearest Neighbour ◽  
Resonance Imaging ◽  
Computerised Tomography ◽  
Medical Field ◽  
Microarray Image ◽  
Image Segementation

Microarray is a fast and rapid growing technology which plays dynamic role in the medical field. It is an advanced than MRI (Magnetic Resonance Imaging) and CT scanning (Computerised Tomography). The purpose of this work is to make fine perfection against the gene expression. In this study the two clustering are used which fuzzy c means and k means and also it classifies with better results. The microarray data base indicates the classification in support vector machine. Segmentation is most important step in microarray image. The classification in support vector machine is compared with other two classifiers which means the k nearest neighbour and with the Bayes classifiers.

scholarly journals Stochastic Reconstruction and Interpolation of Precipitation Fields Using Combined Information of Commercial Microwave Links and Rain Gauges

2017 ◽  
Vol 53 (12) ◽  
pp. 10740-10756 ◽  
Author(s):  
B. Haese ◽  
S. Hörning ◽  
C. Chwala ◽  
A. Bárdossy ◽  
B. Schalge ◽  
...  
Keyword(s):  
Rain Gauges ◽  
Stochastic Reconstruction ◽  
Commercial Microwave Links

scholarly journals Stochastic 3D Carbon Cloth GDL Reconstruction and Transport Prediction

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 572
Author(s):  
Yuan Gao ◽  
Teng Jin ◽  
Xiaoyan Wu
Keyword(s):  
Reconstruction Algorithm ◽  
Gas Diffusion ◽  
Reconstruction Method ◽  
Carbon Cloth ◽  
Statistical Characterization ◽  
Stochastic Reconstruction ◽  
Classical Simulation ◽  
The Many ◽  
Transport Prediction ◽  
Structure Properties

This paper presents the 3D carbon cloth gas diffusion layer (GDL) to predict transport behaviors of anisotropic structure properties. A statistical characterization and stochastic reconstruction method is established to construct the 3D micro-structure using the data from the true materials. Statistics of the many microstructure characteristics, such as porosity, pore size distribution, and shape of the void, are all quantified by image-based characterization. Furthermore, the stochastic reconstruction algorithm is proposed to generate random and anisotropic 3D microstructure models. The proposed method is demonstrated by some classical simulation prediction and to give the evaluation of the transport properties. Various reconstructed GDLs are also generated to demonstrate the capability of the proposed method. In the end, the adapted structure properties are offered to optimize the carbon cloth GDLs.

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