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9th International Conference on Communication, Image and Signal Processing, CCISP 2024

作者： Tan, Yongqun Zhang, Lingli School of Mathematics and Statistics Chongqing Jiaotong University Chongqing400074 China Chongqing University of Arts and Sciences Chongqing Key Laboratory of Statistical Optimization and Complex Data Chongqing402160 China Chongqing University of Arts and Sciences Chongqing Key Laboratory of Group & Graph Theories and Applications Chongqing402160 China

ISBN: (纸本)9798350356656

In recent decades, there has been a notable focus on addressing image deblurring problem. Different deblurring algorithms integrate prior information into the image deblurring model, and the effectiveness of the prior information directly determines the performance of the deblurring. This paper presents a deep optimization image deblurring model based on internal and external information, which is joint with total variation, non-local self-similarity and convolutional neural network. The corresponding algorithm of the presented model utilizes half quadratic splitting method to decouple the fidelity and regularization terms, which can be solved through the sub-problems, respectively. Numerical experiments show that the presented algorithm can outperform the existing algorithms both in preserving the edges and assessment indicators (PSNR, RMSE, and SSIM). © 2024 IEEE.

关键词： optimization algorithms

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Dual-Channel Deep Convolutional Neural Network for Limited-Angle CT Image Restoration 9

Dual-Channel Deep Convolutional Neural Network for Limited-A...

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9th International Conference on Communication, Image and Signal Processing, CCISP 2024

作者： Chen, Yu Zhang, LingLi School of Mathematics and Statistics Chongqing Jiaotong University Chongqing400074 China Chongqing University of Arts and Sciences Chongqing Key Laboratory of Statistical Optimization and Complex Data Chongqing402160 China Chongqing University of Arts and Sciences Chongqing Key Laboratory of Group & Graph Theories and Applications Chongqing402160 China

ISBN: (纸本)9798350356656

Based on the excellent performance of computed tomography (CT) in visualizing the inside of objects, it has become one of the indispensable technologies in the fields of medical diagnosis and industrial inspection. However, due to uncontrollable factors such as radiation dose and detection environment, it is necessary to consider how to obtain projection information within a certain scanning rotation angle range in most cases. In these situations, the reconstructed images using traditional analytical algorithms and iterative algorithms will suffer from limited-angle artifacts. Recently, deep learning technology has gained great attention in the field of image restoration due to its powerful learning ability and its rapid development and application. In order to make up for the limitations of traditional methods in suppressing artifacts in limited-angle CT reconstruction, this paper designs a dual-channel deep convolutional network to remove artifacts in reconstructed images with preserving the details and edges. Simulated and real experiments demonstrate that the presented network can effectively restore images, compared with the classical network. © 2024 IEEE.

关键词： Computerized tomography

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A Deep optimization Image Deblurring Model Based on Internal and External Information

A Deep Optimization Image Deblurring Model Based on Internal...

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Communication, Image and Signal Processing (CCISP), International Conference on

作者： Yongqun Tan Lingli Zhang School of Mathematics and Statistics Chongqing Jiaotong University Chongqing China Chongqing Key Laboratory of Statistical Optimization and Complex Data Chongqing University of Arts and Sciences Chongqing China Chongqing Key Laboratory of Group & Graph Theories and Applications Chongqing University of Arts and Sciences Chongqing China

ISBN: (数字)9798350356656

ISBN: (纸本)9798350356663

关键词： TV Image edge detection Noise Signal processing algorithms Color Gray-scale Image restoration Numerical models Convolutional neural networks optimization

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Dual-Channel Deep Convolutional Neural Network for Limited-Angle CT Image Restoration

Dual-Channel Deep Convolutional Neural Network for Limited-A...

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Communication, Image and Signal Processing (CCISP), International Conference on

作者： Yu Chen LingLi Zhang School of Mathematics and Statistics Chongqing Jiaotong University Chongqing China Chongqing Key Laboratory of Statistical Optimization and Complex Data Chongqing University of Arts and Sciences Chongqing China Chongqing Key Laboratory of Group & Graph Theories and Applications Chongqing University of Arts and Sciences Chongqing China

ISBN: (数字)9798350356656

ISBN: (纸本)9798350356663

关键词： Visualization Attention mechanisms Convolution Computed tomography Splicing Image edge detection Feature extraction Image restoration Convolutional neural networks Image reconstruction

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An age-structured tuberculosis model with information and immigration:Stability and simulation study

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International Journal of Biomathematics 2023年第2期16卷 153-176页

作者： Lili Liu Jian Zhang Yazhi Li Xinzhi Ren Shanci Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention Complea Systems Research Center Shanci University Taiyuan 030006P.R.China Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province School of Mathematics and Statistics Qiannan Normal University for Nationalities Duyun 558000 P.R.China School of Mathematics and Statistics Southwest University Chongqing 400715P.R.China

This paper establishes an age-structured Tuberculosis(TB)model to investigate the joint impacts of information and immigration of population on the spread of TB ***,we show that the model is point dissipative,and the semi-flow generated by the model has the property of asymptotic smoothness,and then study the existence and global stability of positive steady state by the direct Lyapunov ***,by using Matlab software,we verify the theoretical results,and further explore the influence of information(including information coverage and disease-related memory delay)and immigration on the final size of TB *** simulation results show that both information coverage and immigration are positive correlated with the final size of disease,and disease-related memory delay can affect the arrival time of positive steady state,which implies us that improving information coverage,enlarging disease-related memory,and reducing the immigration of population(especially latent and infected individuals)can effectively control the progression of TB disease.

关键词： TB transmission model age-structured information-related immigration global stability.

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Mathematical Analysis of Global Dynamics and Optimal Control of Treatment for an Age-Structured HBV Infection Model

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SSRN 2023年

作者： Liu, Lili Ma, Xiaomin Li, Yazhi Liu, Xianning Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention Complex Systems Research Center Shanxi University Taiyuan030006 China Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou province School of Mathematics and Statistics Qiannan Normal University for Nationalities Guizhou Duyun558000 China School of Mathematics and Statistics Southwest University Chongqing400715 China

Evidences shows that cell-to-cell infection occurs in HBV infection and is a more efficient way which may lead to more than half of viral infection. Hence, we formulate an HBV infection model with cell-to-cell infection, meanwhile, we incorporate the infection age of infected cells. For dynamic behaviors, we firstly establish the well-posedness of the model and asymptotic smoothness of the solution, and then show the global threshold dynamical behaviors, which is determined by the reproduction number, finally perform the numerical simulation not only to verify theoretical results but also explore the effects of cell-to-cell infection on the viral load and infection concentration. Our finding is that ignoring the cell-to-cell infection will underestimate the actually HBV infection status. For optimal control of treatment for HBV, we introduce two time-varying control measures and investigate the corresponding optimal control problem. We derive the characteristic express of optimal control and discuss the effects of control costs and control combination. The results show high control cost will not result in better control effectiveness, while integrated optimal control can reach the best control objectives compared with two single controls, moreover, age can greatly influences the HBV infection at the initial stage. © 2023, The Authors. All rights reserved.

关键词： Cell proliferation

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