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Infrared and Visible Image Fusion Based on Res2Net-Transformer Automatic Encoding and Decoding

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Computers, Materials & Continua 2024年第4期79卷 1441-1461页

作者： chunming wu wukai Liu Xin Ma Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology School of Electrical EngineeringNortheast Electric Power UniversityJilin132012China School of Electrical Engineering Northeast Electric Power UniversityJilin132012China School of Aeronautical Engineering Jilin Institute of Chemical TechnologyJilin132022China

A novel image fusion network framework with an autonomous encoder and decoder is suggested to increase thevisual impression of fused images by improving the quality of infrared and visible light picture fusion. The networkcomprises an encoder module, fusion layer, decoder module, and edge improvementmodule. The encoder moduleutilizes an enhanced Inception module for shallow feature extraction, then combines Res2Net and Transformerto achieve deep-level co-extraction of local and global features from the original picture. An edge enhancementmodule (EEM) is created to extract significant edge features. A modal maximum difference fusion strategy isintroduced to enhance the adaptive representation of information in various regions of the source image, therebyenhancing the contrast of the fused image. The encoder and the EEM module extract features, which are thencombined in the fusion layer to create a fused picture using the decoder. Three datasets were chosen to test thealgorithmproposed in this paper. The results of the experiments demonstrate that the network effectively preservesbackground and detail information in both infrared and visible images, yielding superior outcomes in subjectiveand objective evaluations.

关键词： Image fusion Res2Net-Transformer infrared image visible image

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复杂背景下输电线路缺陷检测算法研究

计算机科学 2024年第S01期51卷 535-540页

作者：邬春明王调君东北电力大学电气工程学院吉林吉林132012

输电线路定期巡检对保障电力系统安全稳定运行具有重要的意义。针对输电线路航拍图像背景复杂、目标尺度变化大、小目标多等问题,提出了基于YOLOv5s的输电线路目标检测算法。该算法采用特征细化模块优化微小目标特征,并在网络中嵌入SimA... 详细信息

输电线路定期巡检对保障电力系统安全稳定运行具有重要的意义。针对输电线路航拍图像背景复杂、目标尺度变化大、小目标多等问题,提出了基于YOLOv5s的输电线路目标检测算法。该算法采用特征细化模块优化微小目标特征,并在网络中嵌入SimAM注意力模块,通过能量函数统一权值的方式优化模型的特征提取,最后引入NWD损失函数削弱模型对小目标位置偏差的敏感性,提升模型对小目标的识别检测能力。实验结果表明,该模型对输电线路目标的平均检测精度高达98.8%,相较于基准模型,提高了1.2%。

关键词：输电线路缺陷检测注意力机制 NWD损失特征细化

一种改进YOLOv5的CT图像肺结节检测方法

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计算机科学 2024年第S01期51卷 575-580页

作者：邬春明刘亚丽东北电力大学电气工程学院吉林吉林132000

针对YOLOv5算法对CT图像中的肺结节检测效果较差的问题,提出基于改进YOLOv5的肺结节检测方法。将YOLOv5网络中Neck部分的特征金字塔改进为加权双向特征金字塔网络;在YOLOv5网络中的Backbone部分加入高效通道注意力机制与坐标注意力机制... 详细信息

针对YOLOv5算法对CT图像中的肺结节检测效果较差的问题,提出基于改进YOLOv5的肺结节检测方法。将YOLOv5网络中Neck部分的特征金字塔改进为加权双向特征金字塔网络;在YOLOv5网络中的Backbone部分加入高效通道注意力机制与坐标注意力机制。在LIDC-IDRI数据集上进行实验,结果表明,检测的平均精度可达80.2%,召回率可达90.75%,因此该方法能够有效检测肺结节。相较于YOLOv5算法,改进后的算法在mAP上提高了7.7%,在召回率上提高了5.5%。

关键词：肺结节检测深度学习特征金字塔注意力机制

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岭南方志音乐史料类别

上海地方志 2024年第2期 65-72,96页

作者：吴春明星海音乐学院广东广州510006

方志中有关音乐的内容零碎、庞杂,无法像专门的音乐图书那样进行整理。为了更好利用方志史料,本文以岭南音乐为例,从资料来源、记录符号、信息层次、专业等进行归类。来源分“风俗”“学校”“艺文”“诸蛮”“政事”等门目;记录符号分... 详细信息

方志中有关音乐的内容零碎、庞杂,无法像专门的音乐图书那样进行整理。为了更好利用方志史料,本文以岭南音乐为例,从资料来源、记录符号、信息层次、专业等进行归类。来源分“风俗”“学校”“艺文”“诸蛮”“政事”等门目;记录符号分图片、乐谱和文字;信息层次分零次、题录和一次文献;专业分“器乐”“歌乐”“曲艺”“戏剧”“舞乐”等。

关键词：岭南方志音乐史料类型

Scheduling Reconfigurable Service Function Chain

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Chinese Journal of Electronics 2019年第6期28卷 1244-1249页

作者： ZHU Kai wu chunming ZHOU Boyang College of Computer Science Zhejiang University Zhejiang Lab

Network function virtualization(NFV),has been widely adopted in existing networks since it brings lower capital expenditure and operating expense,as well as flexible and elastic deployment. Based on NFV, dynamic Service function chain(SFC) provides more comprehensive and thorough traffic steering over a series of middleboxes, e.g., DPI, and IDS. Nevertheless, dynamic SFC involves internal state migration in middleboxes, making it hard to allocate SFC *** propose a reconfigurable SFC scheduling approach with consideration on resource constraints and race of the state migration to collaborate the execution of the SFC reconfiguration, in the reasonable fashion based on a heuristic algorithm. The evaluation is conducted through discrete event simulation to validate the efficiency of our reconfigurable SFC scheduling, and the results demonstrate that the proposed method outperforms First Come First Serve scheduling and random scheduling.

关键词： Network function virtualization(NFV) Service function chain(SFC) State migration SDN

A multipath resource updating approach for distributed controllers in software-defined network.

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Science China(Information Sciences) 2016年第9期59卷 227-236页

作者： Xiaochun wu chunming wu Changting LIN Qiang wu Bin WANG Computer Science College Zhejiang University Institute of Network and Communication Engineering Zhejiang Gongshang University ZTE Central R&D ZTE Corporation

Finding effective ways to collect the usage of network resources in all kinds of applications to ensure a distributed control plane has become a key requirement to improve the controller’s decision making *** paper explores an efficient way in combining dynamic Net View sharing of distributed controllers with the behavior of intra-service resource announcements and processing requirements that occur in distributed controllers, and proposes a rapid multipathing distribution mechanism. Firstly, we establish a resource collecting model and prove that the prisoner’s dilemma problem exists in the distributed resource collecting process in the Software-defined Network(SDN). Secondly, we present a bypass path selection algorithm and a diffluence algorithm based on Q-learning to settle the above dilemma. At last, simulation results are given to prove that the proposed approach is competent to improve the resource collecting efficiency by the mechanism of self-adaptive path transmission ratio of our approach, which can ensure high utilization of the total network we set up.

关键词： multipath Pareto optimal Q-learning

Metrics in Sharing Video Relationship-Networks

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Chinese Journal of Electronics 2014年第3期23卷 598-603页

作者： GAO Wen QIAN Yaguan wu chunming College of Computer Science & Technology Zhejiang University College of Science Zhejiang University of Science and Technology

At present the video sharing service has gradually became one of the Internet killer applications. It is crucial to the service providers that understand the intrinsic nature of Sharing video relationship-networks(SVRNs) formed by video related list. This paper investigates the relationships between sharing videos using complex networks theory. New metrics are introduced to model and characterize the SVRN from topological view. Through extensive study on You Tube, a set of key findings are revealed. The results show that the node indegree of SVRNs follows the power-law distribution and its entropy remains stable over time. The topology also exhibits an assortative property and obvious clustering phenomenon. But the rich-club phenomenon is not evident compared with the Internet AS-level topology. This research will enable the service providers to optimally plan and operate their video-based services.

关键词： Video sharing services Video relationship-networks Topological characteristics Complex networks

基于近似测量算法Sketch的高精度区块链异常检测机制

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计算机研究与发展 2024年第10期61卷 2526-2539页

作者：朱龙隆陈翔陈浩东牛继堂刘雯靓林声睿张栋吴春明福州大学计算机与大数据学院浙江大学计算机科学与技术学院泉城实验室浙江大学工程师学院浙江广播电视集团

区块链存在网络动态性强和其管理困难等问题，使得区块链普遍存在DDo S攻击和账户接管等异常现象.现有区块链异常检测方法多从所有区块链账户中提取历史交易信息和交易频率等特征加以分析以甄别异常.然而，随着区块链数据规模的不断扩... 详细信息

区块链存在网络动态性强和其管理困难等问题，使得区块链普遍存在DDo S攻击和账户接管等异常现象.现有区块链异常检测方法多从所有区块链账户中提取历史交易信息和交易频率等特征加以分析以甄别异常.然而，随着区块链数据规模的不断扩大，现有方法在提取特征时面临内存消耗高、检测精度低的挑战.为此，提出了一种高检测精度、低内存开销的区块链异常检测机制，该机制采用近似测量算法将区块链异常检测转化为异常交易账户检测，包括区块内异常账户和跨区块异常账户.对于区块内异常账户，即仅存在于单个区块内的异常账户，使用Sketch算法进行账户识别，精度高.而对于存在于多个区块且难以通过单个区块信息检测到的跨区块异常账户，则通过聚合和分析多区块信息进行账户的准确检测.使用包含88 847个区块的真实区块链数据评估上述机制.实验结果表明，与现有代表性方法对比，所提出的机制将区块链异常检测的召回率最高提升了6.3倍，F1分数最高提升了4.4倍.因此，提出的高精度区块链异常检测机制对于规范区块链交易行为、维护系统安全性具有意义.

关键词：区块链安全异常检测近似算法 Sketch

Intelligent Orchestrating of IoT Microservices Based on Reinforcement Learning

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Chinese Journal of Electronics 2022年第5期31卷 930-937页

作者： wu Yuqin SHEN Congqi CHEN Shuhan wu chunming LI Shunbin WEI Ruan College of Computer Science and Technology Zhejiang University College of Information and Electrical Engineering Ningde Normal University Zhejiang Lab College of Control Science and Engineering Zhejiang University

With the recent increase in the number of Internet of things(IoT) services, an intelligent scheduling strategy is needed to manage these services. In this paper, the problem of automatic choreography of microservices in IoT is explored. A type of reinforcement learning(RL) algorithm called TD3 is used to generate the optimal choreography policy under the framework of a softwaredefined network. The optimal policy is gradually reached during the learning procedure to achieve the goal, despite the dynamic characteristics of the network environment. The simulation results show that compared with other methods, the TD3 algorithm converges faster after a certain number of iterations, and it performs better than other non-RL algorithms by obtaining the highest reward. The TD3 algorithm can effciently adjust the traffic transmission path and provide qualified IoT services.

关键词： Internet of things Microservice Traffc scheduling Reinforcement learning