检索结果-内蒙古大学图书馆

Joint Deep Matching Model of OCT Retinal Layer Segmentation

Computers, Materials & Continua 2020年第6期63卷 1485-1498页

作者： Mei Yang Yuanjie Zheng Weikuan Jia Yunlong He Tongtong Che Jinyu Cong School of Information Science and Engineering at Shandong Normal University Jinan250358China Key Lab of Intelligent Computing and Information Security in Universities of Shandong Shandong Provincial Key Laboratory for Novel Distributed Computer Software TechnologyInstitute of Biomedical SciencesShandong Normal UniversityJinan250358China INSA Lyon University of LyonCNRSInsermVilleurbanne69621 CedexFrance

Optical Coherence Tomography(OCT)is very important in medicine and provide useful diagnostic *** retinal layer thicknesses plays a vital role in pathophysiologic factors of many ocular *** the existing retinal layer segmentation approaches,learning or deep learning-based methods belong to the ***,most of these techniques rely on manual-marked layers and the performances are limited due to the image *** order to overcome this limitation,we build a framework based on gray value curve matching,which uses depth learning to match the curve for semi-automatic segmentation of retinal layers from *** depth convolution network learns the column correspondence in the OCT image *** whole OCT image participates in the depth convolution neural network operation,compares the gray value of each column,and matches the gray value sequence of the transformation column and the next *** this algorithm,when a boundary point is manually specified,we can accurately segment the boundary between retinal *** experimental results obtained from a 54-subjects database of both normal healthy eyes and affected eyes demonstrate the superior performances of our approach.

关键词： OCT retinal segmentation deep learning 1D convolution

来源：评论

学校读者我要写书评

暂无评论

ASRNet: Adversarial Segmentation and Registration Networks for Multispectral Fundus Images

引用

Computer Systems Science & Engineering 2021年第3期36卷 537-549页

作者： Yanyun Jiang Yuanjie Zheng Xiaodan Sui Wanzhen Jiao Yunlong He Weikuan Jia School of Information Science and Engineering Shandong Normal UniversityJinan250358China Key Laboratory of Intelligent Computing&Information Security in Universities of Shandong Shandong Provincial Key Laboratory for Novel Distributed Computer Software TechnologyInstitute of Biomedical SciencesShandong Normal UniversityJinan250358China Shandong Provincial Hospital Affiliated to Shandong University Jinan250021China INSA Lyon University of LyonCNRSInsermVilleurbanne69621CedexFrance

Multispectral imaging (MSI) technique is often used to capture imagesof the fundus by illuminating it with different wavelengths of light. However,these images are taken at different points in time such that eyeball movementscan cause misalignment between consecutive images. The multispectral imagesequence reveals important information in the form of retinal and choroidal bloodvessel maps, which can help ophthalmologists to analyze the morphology of theseblood vessels in detail. This in turn can lead to a high diagnostic accuracy of several diseases. In this paper, we propose a novel semi-supervised end-to-end deeplearning framework called “Adversarial Segmentation and Registration Nets”(ASRNet) for the simultaneous estimation of the blood vessel segmentation andthe registration of multispectral images via an adversarial learning process. ASRNet consists of two subnetworks: (i) A segmentation module S that fulfills theblood vessel segmentation task, and (ii) A registration module R that estimatesthe spatial correspondence of an image pair. Based on the segmention-drivenregistration network, we train the segmentation network using a semi-supervisedadversarial learning strategy. Our experimental results show that the proposedASRNet can achieve state-of-the-art accuracy in segmentation and registrationtasks performed with real MSI datasets.

关键词： Deep learning deformable image registration image segmentation multispectral imaging(MSI)

来源：评论

学校读者我要写书评

暂无评论

Effects of Plasma Density Profile on Resistive Wall Mode Stability

引用

Journal of Donghua University(English Edition) 2017年第5期34卷 635-640页

作者：陈龙溪孟祥佳王进芳 School of Information Engineering Shandong Youth University of Political ScienceJinan 250103China Key Lab of Information Security and Intelligent Control in Universities of Shandong Jinan 250103China Institute of Plasma Physics Chinese Academy of SciencesHefei 230031China

Linear and nonlinear evolutions of the resistive wall mode(RWM) were numerically carried out with different plasma density *** stabilizing and destabilizing effects were *** plasma density shear had a stabilizing effect on the RWM,and the stabilizing effect was better as the plasma density shear rate *** the uniform density plasma,the effects of flowshear on the RWMstability were stronger than those for non-uniform density *** lower flowshear,the effects of the plasma density shear rate on the RWMwere more *** the nonlinear phase,the repulsive force associated with the piling up magnetic flux near the resistive wall prevented further growth of perturbed magnetic energy,and the RWMwas *** saturation levels were almost independent of the density profiles.

关键词： resistive wall mode(RWM) density profile stability saturation

来源：评论

学校读者我要写书评

暂无评论

Epilepsy Classification for Mining Deeper Relationships between EEG Channels based on GCN

Epilepsy Classification for Mining Deeper Relationships betw...

引用

2020 International Conference on Computer Vision, Image and Deep Learning, CVIDL 2020

作者： Chen, Xin Zheng, Yuanjie Niu, Yi Li, Chengiiang Shandong Normal University School of Information Science and Engineering Jinan250358 China Key Lab of Intelligent Computing and Information Security Universities of Shandong Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Institute of Biomedical Sciences Jinan250358 China Department of Electrical Engineering Information Technology Shandong University of Science and Technology Jinan250031 China

ISBN: (纸本)9781728194813

Epilepsy is a brain disorder caused by abnormal discharges of neurons in brain. It is one of the most commonly studied disorders in neurology. The research of epilepsy electroencephalogram (EEG) has become a hot research topic. We find that in epilepsy EEG detection task, many previous methods focused on directly collecting the data of each channel, but these methods seldom analyse relationships between signals. Therefore, we propose the Epilepsy EEG Graph Convolutional Network EGCN, which makes full use of correlations between channels to deeply mine data information. We specifically design 5-layer graph convolutional network structure for classification of healthy and epileptic patients. The method is applied to public data set (Boon and CHB-MIT) to establish a reasonable classification model. And we compare it with some advanced algorithms. The experimental results show that the E-GCN method is superior to many existing methods in classification accuracy. In brief, the E-GCN method can be effectively used in classification and detection for epilepsy. This provides new ideas for colleagues, who study epilepsy EEG. In addition, this also provides richer experience for diagnosis of epilepsy. © 2020 IEEE.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Effects of Magnetic Shear on the Resistive Wall Mode Instability in a Cylindrical Model

引用

Journal of Donghua University(English Edition) 2019年第6期36卷 533-538页

作者： CHEN Longxi WANG Jinfang WANG Lifeng YANG Zhiran School of Information Engineering Shandong Youth University of Political ScienceJi'nan 250103China Key Lab of Information Security and Intelligent Control in Universities of Shandong Ji’nan 250103China Institute of Plasma Physics Chinese Academy of SciencesHefei 230031China

The linear evolution of a resistive wall mode(RWM)with magnetic shears was analytically studied in a cylindrical *** incompressible magnetohydrodynamic(MHD)equations were solved by the Fourier analysis method,and various equilibrium magnetic fields were *** shear in the magnetic field had an unstable effect on the linear evolution of the *** linear growth rate increased obviously with increase of the magnetic shear rate for higher magnetic *** plasma rotation could stabilize the RWM with low magnetic shears,but the plasma rotation could not stabilize the RWM with high magnetic *** stabilizing effects of the wall conductivity on the RWM are more efficient for lager magnetic shear.

关键词： resistive wall mode(RWM) cylindrical model magnetic shear

来源：评论

学校读者我要写书评

暂无评论

Expectation-Constrained Programming Model for Tourist Route of Attractions Based on Uncertainty Theory 5

Expectation-Constrained Programming Model for Tourist Route ...

引用

5th International Conference on Advanced Electronic Materials, Computers and Software Engineering, AEMCSE 2022

作者： Huang, Zheng Ning, Yufu Liu, Fengming Shandong Normal University Business School Ji'nan China Key Lab. of Intelligent Information Processing Technology and Security in Universities of Shandong Jinan250103 China Shandong Youth University of Political Science School of Information Engineering Ji'nan China

ISBN: (数字)9781665484749

ISBN: (纸本)9781665484749

Based on the current background of scenic spot management and tourism planning in China, this paper establishes an uncertain tourism route expectation-constrainted programming model under the framework of uncertainty theory. Finally, eight attractions in Jinan are used as practical cases to illustrate the usefulness of the model. The research results show that the proposed model can effectively alleviate the problems of unreasonable allocation of tourists' time and cost in the traditional model, and make the layout and programming of routes more reasonable and efficient. © 2022 IEEE.

关键词： Computer programming

来源：评论

学校读者我要写书评

暂无评论

Exploiting Probabilistic Siamese Visual Tracking with a Conditional Variational Autoencoder

Exploiting Probabilistic Siamese Visual Tracking with a Cond...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Wenhui Huang Jason Gu Peiyong Duan Sujuan Hou Yuanjie Zheng School of Information Science and Engineering Shandong Normal University China Dalhousie University Halifax Canada Key Lab of Intelligent Computing & Information Security in Universities of Shandong Shandong Normal University China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Shandong Normal University China

Visual tracking is a fundamental capability for robots tasked with humans and environment interaction. However, state-of-the-art visual tracking methods are still prone to failures and are imprecise when applied to challenging stereos, and their results are generally confidence agonistic. These methods depend on an embedded deep learning model to provide deterministic features or regression maps. A deterministic output with low confidence can result in disastrous consequences and lacks evidence needed for subsequent operations. Moreover, training data ambiguities or noise in the observations (so-called data uncertainty) can also lead to inherent uncertainty. In this paper, we focus on exploiting probabilistic Siamese visual tracking with a conditional variational autoencoder (CVAE). First, we build a bridge between the Siamese architecture and the CVAE and propose a novel Bayesian visual tracking method. Second, the proposed method generates a complete probability distribution that enables the production of multiple plausible tracking outputs. Third, CVAE conditioned by ground truth data encodes a low-dimensional latent space and conducts noise-injection training to prevent overfitting. Our proposed tracking method outperformed the state-of-the-art trackers on the VOT2016, VOT2018 and TColor-128 datasets.

关键词： Bridges Training Visualization Uncertainty Training data Probabilistic logic Probability distribution

来源：评论

学校读者我要写书评

暂无评论

Design of People Flow Monitoring System in Public Place based on MD-MCNN

Design of People Flow Monitoring System in Public Place base...

引用

2020 International Conference on 5G Mobile Communication and information Science, MCIS-5G 2020

作者： Tianmin, Xiong Xiaochun, Lei Xingwen, Zheng Junyan, Chen Yizhou, Feng School of Computer and Information Security Guilin University of Electronic Technology Guilin541004 China Guangxi Colleges and Universities Key Lab. of Intelligent Processing of Computer Images and Graphics Guilin541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 China

Due to the limitation of hardware resources, the traditional people flow monitoring system based on computer vision in public places can't meet different crowd-scale scenarios. Therefore, a people flow monitoring system based on MD-MCNN algorithm is designed, which is an application system combining the improved SSD object detection algorithm MNSSD and MCNN density map regression algorithm. In the initial stage, the system uses MNSSD for accurate detection and counting. If the people flow gradually reaches a certain threshold, the system automatically uses MCNN to estimate people flow until the people flow falls below the threshold. Through the experimental verification, the system can realize the people flow statistics of low-density and high-density people in different scenarios, and can be applied on the existing embedded platform. This scheme can be extended to smart cities, smart scenic spots, smart transportation and other fields. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Design of intelligent Robot Platform based on Multi-sensor Fusion

Design of Intelligent Robot Platform based on Multi-sensor F...

引用

2020 International Conference on 5G Mobile Communication and information Science, MCIS-5G 2020

作者： Dajin, Ya Xiaochun, Lei Yue, Li Junyan, Chen Rongcun, Huang Lin, Lan School of Computer and Information Security Guilin University of Electronic Technology Guilin541004 China Guangxi Colleges and Universities Key Lab. of Intelligent Processing of Computer Images and Graphics Guilin541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 China

The mobile robot adapts to the more complicated indoor and outdoor environments, and can expand its scope of application. In order to reduce the influence of the cumulative error caused by navigation in complex environments, the indoor mobile robot that combines Inertial Measurement Unit (IMU) and encoder fusion is designed and implemented. In view of the limitations of the traditional single lidar scheme, a Multi-sensor Fusion scheme is proposed to achieve indoor map construction, path planning, multi-point navigation and other functions, and a MSIF KartoSLAM (Multi-sensor information Fusion) algorithm is proposed, which combines the KartoSLAM algorithm and Multi-sensor information to achieve map construction in complex environments. Through comprehensive testing in the indoor environment, the results show that the Multi-sensor Fusion scheme is superior to the traditional single lidar scheme, and can achieve higher accuracy in mapping and navigation. At the same time, the robot platform can also be combined with the Internet of Things technology and integrated into intelligent housing system. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Navigation

来源：评论

学校读者我要写书评

暂无评论

Epilepsy Classification for Mining Deeper Relationships between EEG Channels based on GCN

Epilepsy Classification for Mining Deeper Relationships betw...

引用

Computer Vision, Image and Deep Learning (CVIDL), International Conference on

作者： Xin Chen Yuanjie Zheng Yi Niu Chengiiang Li School of Information Science and Engineering Shandong Normal University Jinan China Key Lab of Intelligent Computing and Information Security Universities of Shandong Jinan China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Institute of Biomedical Sciences Jinan China Shandong University of Science and Technology Jinan China

ISBN: (数字)9781728194813

ISBN: (纸本)9781728194820

关键词： Epilepsy Electroencephalography Convolution Brain modeling Feature extraction Correlation Task analysis

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：