检索结果-内蒙古大学图书馆

2020 International Symposium on Automation, Information and Computing, ISAIC 2020

作者： Xu, Changchang Hu, Dong Zhang, YaoDong Pang, Yuwei Jiangsu Province’s Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications Nanjing210003 China Education Ministry’s Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing210003 China Education Ministry’s Engineering Research Center of Ubiquitous Network and Heath Service Nanjing University of Posts and Telecommunications Nanjing210003 China first clinical medical college of Nanjing Medical University Nanjing University of Posts and Telecommunications Nanjing210003 China

As a common malignant tumor disease, hepatocellular carcinoma is the most common cancers in the world. The incidence of hepatocellular carcinoma in China is higher than that in the world. Therefore, it is very important for doctors to separate liver and tumor from CT images by means of computer-aided diagnosis and treatment. In this paper, a multiscale DC-CUNets network liver tumor segmentation method is proposed to enhance the fusion of multi-phase image features in CT, the scale of liver tumors, and the optimization of network training process. (1) A multistage CT liver tumor segmentation method based on two-channel cascaded U-Nets (DC-CUNets) is proposed. The liver was segmented using the first-order U-Net, and then the segmented area of interest of the liver was input into the second-order U-Net network to segment liver tumors. We designed two-channel U-Nets to learn the image characteristics of CT images in arterial and venous phases respectively, and to achieve two-channel feature fusion through feature cascade to improve the overall accuracy of liver tumor segmentation.(2) A multistage CT liver tumor segmentation method based on multiscale DC-CUNets was proposed. For the scale problem of liver tumors, we designed a two-layer multiscale void convolution module to obtain image features at different scales for large, medium and small tumors, and fuse the multiscale features at the output of the module. We have replaced the convolution layer of the fourth module in the second-order two-channel liver tumor segmentation U-Nets by the two-layer multiscale cavity convolution module to implement multiscale DC-CUNets. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

SiamIRPN: Siamese Visual Tracking with Improved Region Proposal networks

SiamIRPN: Siamese Visual Tracking with Improved Region Propo...

引用

Frontiers of Robotics and Software Engineering (FRSE), International Conference on

作者： Dun Cao Renhua Dai Tianyu Zhao Fayez Alqahtani Amr Tolba R. Simon Sherratt Min Zhu School of Computer and Communications Engineering Changsha University of Science and Technology Changsha Hunan China Key Lab of Broadcast Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Software Engineering Department College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia Computer Science Department Community College King Saud University Riyadh Saudi Arabia School of Biomedical Engineering The University of Reading United Kingdom College of Information Science and Technology Zhejiang Shuren University Zhejiang China

Though introducing the Region Proposal network (RPN) from object detection enabled Siamese trackers’ success, RPN-based trackers still struggle in challenging scenarios. We posit that the reason comes from two major limitations of the introduced RPN, where one is that the external structure of the RPN is simple and straight, the other is that the internal components used in RPN cannot cope with complex scenes. In this paper, we propose an Improved RPN (IRPN) suitable for visual tracking. Externally, we place a Convolutional Block Attention Mechanism (CBAM) to the IRPN, and internally, we adopt the advanced component groups for the IPRN. Using multiple IRPN blocks and deep architecture, we propose a Siamese tracker (SiamIRPN) having a layer-wise structure. Comprehensive experiments and ablation studies on five benchmarks (VOT-2019, OTB100, UAV123, GOT-10k, and NFS) show our proposed SiamIRPN achieves competitive performance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Dynamic embedding and scheduling of virtual network service for future networks

Dynamic embedding and scheduling of virtual network service ...

引用

2019 IEEE International Conference on communications Workshops, ICC Workshops 2019

作者： Cao, Haotong Zhang, Yao Yang, Longxiang Key Lab of Broadband Wireless Communications and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781728123738

Software defined networking (SDN) and network function virtualization (NFV) are two most promising approaches for implementing the network virtualization. Traditional Internet will be transformed into SDN/NFV-enabled networks in the future. Through virtualization, the heterogeneous underlying resources enable to provide agile and customized virtual network (VN) services to end users. However, virtual network function (VNF) embedding and scheduling are crucial to the VN service deployment in the SDN/NFV-enabled networks. In this paper, dynamic VNF embedding and scheduling are jointly investigated for enhancing the VN service provisioning. At first, the VNF embedding and scheduling problem is formulated, using mixed integer linear programming (MILP) approach. Then, a dynamic VNF embedding and scheduling algorithm is proposed. For instance, when a new VN service is requested, the VNFs, constituting the service function chain (SFC) of the VN service, will be embedded and scheduled by the proposed algorithm. If the resource and QoS requirements of the VNFs are not satisfied, a re-embedding and re-scheduling scheme will be triggered. Certain VNFs will be re-embedded and re-scheduled. The dynamic embedding and scheduling have flexible network function placement and improves the underlying resource utilization. Finally, simulation results are illustrated. © 2019 IEEE.

关键词： network function virtualization

来源：评论

学校读者我要写书评

暂无评论

Energy Efficiency Optimization in Heterogeneous networks Based on Deep Reinforcement Learning

Energy Efficiency Optimization in Heterogeneous Networks Bas...

引用

IEEE International Conference on communications Workshops, ICC

作者： Daoping Shi Feng Tian Shengchen Wu Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing Universityof Posts and Telecommunications) Ministry of Education Nanjing China Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (数字)9781728174402

ISBN: (纸本)9781728174419

To meet the rapid increasing requirement of service and application of communication, heterogeneous wireless networks with the macrocell and the femtocells are considered in this paper. How to deal with resource allocation efficiently and dynamically in heterogeneous wireless networks puts forward to an urgent problem. In this paper, we aim to maximize the overall network's energy efficiency, where multiple femto base stations are randomly and densely distributed in the coverage of macro base station. We first construct an EE model and formulate the problem for optimization. Then we propose a Nature DQN algorithm in deep reinforcement learning to solve it with power discretization. Finally, in simulations, it demonstrates that the proposed Nature DQN can not only achieve better energy efficiency than Q-learning and water-filling but also accelerate the convergence.

关键词： Optimization Resource management Macrocell networks wireless networks Machine learning Femtocells Interference

来源：评论

学校读者我要写书评

暂无评论

Energy-optimized 5G dual connectivity radio resource allocation 2

Energy-optimized 5G dual connectivity radio resource allocat...

引用

2nd IEEE International Conference on Electronics technology, ICET 2019

作者： Ying, Guo Qingmin, Meng Xiaoming, Wang Ministry of Education College of Telecommunications Information Engineering Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China National Mobile Communications Research Lab Southeast University Nanjing210096 China

ISBN: (纸本)9781728116181

Non-independent networking of 5G NSA (Non-Standalone) is receiving wide attention. This paper considers an NSA architecture in which a 4G base station is used as the primary station and a newly deployed 5G base station is used as the secondary station. Machine-type communication and vehicle networking applications place stringent requirements on end-to-end delay of 5G NSA like systems. Due to limited computing power, part of the terminal data needs to be uploaded to the edge cloud to perform intensive calculations. An optimized radio resource allocation scheme is proposed for dual connectivity transmission under 5G NSA. Second, the relevant handover strategies are also evaluated. Computer simulation results show that compared with single-connection transmission, dual-connection transmission can significantly improve the energy consumption performance of the transmission scheme under a time delay constraint. © 2019 IEEE.

关键词： Mobile edge computing

来源：评论

学校读者我要写书评

暂无评论

A coalitional game based user access algorithm in energy-harvesting small cell networks 18

A coalitional game based user access algorithm in energy-har...

引用

2018 18th IEEE International Conference on Communication technology, ICCT 2018

作者： Wang, Xueting Izhu, Q. Nanjing University of Posts and Telecommunications Jiangsu Province Key Laboratory of Wireless Communications Key Laboratory on Wideband Wireless Communications and Sensor Network Technology of Ministry of Education Nanjing China

ISBN: (纸本)9781538676349

To improve the users' satisfaction of downloading files, a cache based resource allocation algorithm in energy-harvesting small cell networks is proposed, which is established as a coalitional game and users try to switch between coalitions with satisfaction as utility function. The switch is accepted once the utilities of user and coalition after switching satisfies the switch orders. This algorithm also allows multi users to be served by a same small cell sharing the same channel using Non-orthogonal Frequency Division Multiple Access (NOMA). The simulation results show that our novel algorithm performs better on user satisfaction. © 2018 IEEE.

关键词： Energy harvesting

来源：评论

学校读者我要写书评

暂无评论

Voiceprint recognition based on BP Neural network and CNN 4

Voiceprint recognition based on BP Neural Network and CNN

引用

2019 4th International Conference on Intelligent Computing and Signal Processing, ICSP 2019

作者： Zhipeng, Dong Jingcheng, Wei Yumin, Xu Qingmin, Meng Xiaoming, Wang Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education College of Telecommunications and Information Engineering Nanjing210003 China National Mobile Communications Research Lab Southeast University Nanjing210096 China

At present, speech recognition has become a key technology of human-computer interaction, which can be used in semantic recognition and speaker identification and other related applications. This paper focuses on a speaker identification scene and the technical design. Because artificial neural network has the ability to distinguish complex classification boundaries, plenty of work on speech recognition had studied multi-layer perceptual networks to improve the accuracy of classification where back propagation method (BP algorithm) has been used. In the studied scheme, when the test objects (speakers) speak the same isolated word, the identification system can judge who the speaker is by identifying the voice voiceprint of different people. Our design not only considers the recognition based on BP as well as its variant, but also explores the voiceprint recognition based on convolution neural network (CNN). Secondly, the network structure and performance are also compared in detail. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Speech recognition

来源：评论

学校读者我要写书评

暂无评论

Universal multi-source domain adaptation

arXiv

引用

arXiv 2020年

作者： Yin, Yueming Yang, Zhen Hu, Haifeng Wu, Xiaofu Nanjing University of Posts and Telecommunications Nanjing210003 China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing210003 China National Engineering Research Center of Communications and Networking Nanjing University of Posts and Telecommunications Nanjing210003 China

Unsupervised domain adaptation enables intelligent models to transfer knowledge from a labeled source domain to a similar but unlabeled target domain. Recent study reveals that knowledge can be transferred from one source domain to another unknown target domain, called Universal Domain Adaptation (UDA). However, in the real-world application, there are often more than one source domain to be exploited for domain adaptation. In this paper, we formally propose a more general domain adaptation setting, universal multi-source domain adaptation (UMDA), where the label sets of multiple source domains can be different and the label set of target domain is completely unknown. The main challenges in UMDA are to identify the common label set between each source domain and target domain, and to keep the model scalable as the number of source domains increases. To address these challenges, we propose a universal multi-source adaptation network (UMAN) to solve the domain adaptation problem without increasing the complexity of the model in various UMDA settings. In UMAN, we estimate the reliability of each known class in the common label set via the prediction margin, which helps adversarial training to better align the distributions of multiple source domains and target domain in the common label set. Moreover, the theoretical guarantee for UMAN is also provided. Massive experimental results show that existing UDA and multi-source DA (MDA) methods cannot be directly applied to UMDA and the proposed UMAN achieves the state-of-the-art performance in various UMDA settings. Copyright © 2020, The Authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

A Smart Content Caching and Replacement Scheme for UAV-Assisted Fog Computing network

A Smart Content Caching and Replacement Scheme for UAV-Assis...

引用

International Conference on wireless communications and Signal Processing (WCSP)

作者： Xujie Li Jichang Shen Ying Sun Ziya Wang Xuedong Zheng College of Computer and Information Engineering Hohai University Nanjing China National Mobile Communications Research Laboratory Southeast University Nanjing China Key Lab for Wireless Sensor network and Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China Nanjing China-Spacenet Satellite Telecom Co.Ltd China

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

For unmanned aerial vehicle (UAV)-assisted fog computing system, content caching is an effective way to reduce network delay. How to smartly sense the future requirement of the user equipment and cache the contents in advance is a big challenge. Meanwhile, the impact of cache content size and other related factors on cache performance are often overlooked, which results in low cache hit ratio. Therefore, this paper proposes a smart caching and caching replacement scheme based on valuation function of content caching for UAV-assisted fog computing network. Firstly, the effect of the content popularity, content size and available cache storage space on system performance is analysed. Then the valuation function combing these factors is defined. Based on the presented valuation function, a smart content caching and caching replacement scheme for UAV-assisted fog computing network is proposed. Finally, the simulation results validate the effectiveness of the proposed scheme. The scheme can be applied into the design the deployment of the UVA-assisted fog computing network.

关键词： Edge computing Cost accounting Unmanned aerial vehicles Performance evaluation Delays Indexes Quality of service

来源：评论

学校读者我要写书评

暂无评论

Delay Optimization Based on Improved Differential Evolutionary Algorithm for Task Offloading in Fog Computing networks

Delay Optimization Based on Improved Differential Evolutiona...

引用

International Conference on wireless communications and Signal Processing (WCSP)

作者： Xujie Li Guangzhao Zhang Xuedong Zheng Siyang Hua College of Computer and Information Hohai University Nanjing China National Mobile Communications Research Laboratory Southeast University Nanjing China Key Lab for Wireless Sensor network and Communication Chinese Academy of Sciences Shanghai China Nanjing China-Spacenet Satellite Telecom Co. Ltd Nanjing China Talent Science and Technology Co. Ltd Nanjing China

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

With the rapid development of communication technology, more and more devices tend to be intelligent. Intelligent devices with computing functions can provide computing services to reduce total task completion time in fog computing networks. This paper aims at minimizing the total task completion time to study multi-user multi-node multi-task offloading problem. Firstly, the task offloading process of task node and fog node is modeled. Then, the system function of the total task completion time is constructed and an optimization problem with constraints is generated. The problem is NP-hard and difficult to be solved by traditional methods. Finally, the improved differential evolution (IDE) algorithm is used to solve the task offloading problem. Simulation results show that it has better performance and can significantly shorten the total task completion time compared with other algorithms.

关键词： Task analysis Delays Computational modeling Edge computing Optimization Signal to noise ratio wireless communication

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：