Affine Deformation Model Based Intra Block Copy for Intra Frame Coding

2020 ◽  
Author(s):  
Daowen Li ◽  
Zhihao Zhang ◽  
Kaitian Qiu ◽  
Yaqing Pan ◽  
Yingming Li ◽  
...  
Keyword(s):  
Deformation Model ◽  
Model Based ◽  
Affine Deformation

Super-resolution reconstruction and higher-degree function deformation model based matching for Chang’E-1 lunar images

2009 ◽  
Vol 52 (12) ◽  
pp. 3468-3476 ◽  
Author(s):  
LiChun Li ◽  
QiFeng Yu ◽  
Yun Yuan ◽  
Yang Shang ◽  
HongWei Lu ◽  
...  
Keyword(s):  
Super Resolution ◽  
Deformation Model ◽  
Model Based ◽  
Degree Function

A Blood Vessel Deformation Model Based Virtual-reality Simulator for the Robotic Catheter Operating System

2015 ◽  
Vol 2 (3) ◽  
pp. 126-131 ◽  
Author(s):  
Yu Wang ◽  
Shuxiang Guo ◽  
Takashi Tamiya ◽  
Hideyuki Hirata ◽  
Hidenori Ishihara
Keyword(s):  
Operating System ◽  
Virtual Reality ◽  
Blood Vessel ◽  
Deformation Model ◽  
Virtual Reality Simulator ◽  
Model Based

Study of Dam Deformation Model Based on Neural Network

2012 ◽  
Vol 170-173 ◽  
pp. 2137-2142 ◽  
Author(s):  
Wu Sheng Hu ◽  
Fan Zhang ◽  
Lei Song ◽  
Hao Wang
Keyword(s):  
Neural Network ◽  
Statistical Model ◽  
Network Model ◽  
Neural Network Model ◽  
Bp Neural Network ◽  
Deformation Analysis ◽  
Deformation Model ◽  
Model Based ◽  
Dam Deformation ◽  
Bp Neural Network Model

Dam deformation analysis is one of the main tasks in dam safety monitoring. Regression analysis model is often used in dam deformation analysis in early days. At present, the statistical model, which divides the dam deformation into three parts, hydraulic pressure component, thermal component and ageing component, according to the causes of deformation, has been widely adopted in dam deformation analysis. The BP neural network model and the merging model based on BP neural network algorithm of dam deformation analysis are mainly discussed in this paper, and finally, the four models mentioned above are calculated and analyzed according to a specific project instance. The precisions are respectively ±1.19mm, ±0.38mm, ±0.34mm, and ±0.28mm for single linear regression model, statistical model, BP neural network model and merging model. So it is shown that the merging model is better than the others according to the results.

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