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Ship Target Detection Algorithm Based on Improved YOLOv5

Ship Target Detection Algorithm Based on Improved YOLOv5

computer Science, Electronic Information engineering and Intelligent Control Technology (CEI), IEEE International Conference on

作者： Louyu Zhu Zhenbo Bi School of Information Engineering Zhejiang Ocean University Zhoushan China Department of Physics and Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province Zhejiang Ocean University Zhoushan China

ISBN: (数字)9798350372052

ISBN: (纸本)9798350372069

In view of the low accuracy and low efficiency of traditional ship target detection methods, this paper introduces an improved ship target detection method based on YOLOv5. Firstly, we preprocess the ship target data set, which includes graph denoising, graph enhancement and so on. Secondly, based on the benchmark YOLOv5 object detection algorithm, SimAM attention mechanism module is introduced. Then, a pyramid feature fusion strategy is added to filter conflicting information in airspace to suppress inconsistent features and improve the network's feature fusion capability for targets of different scales. Finally, the trained model is tested to achieve accurate evaluation of ship target detection. Experimental results show that the proposed ship target detection method is compared with YOLOv5s in accuracy rate, recall rate, mAP@0.5 and mAP@0.5: 0.95 increased by 1.9, 3.8, 2.6 and 7.3 percentage points. Respectively, which can meet the requirements of detection speed and obtain better detection accuracy, effectively realizing high-speed and high-precision ship detection.

关键词： YOLO computer science Noise reduction Filtering algorithms Benchmark testing Information filters Robustness

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Continual Reinforcement Learning for Digital Twin Synchronization Optimization

引用

IEEE Transactions on Mobile Computing 2025年

作者： Tong, Haonan Chen, Mingzhe Zhao, Jun Hu, Ye Yang, Zhaohui Liu, Yuchen Yin, Changchuan Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing Advanced Information Network Laboratory Beijing China College of Computing and Data Science Singapore University of Miami Department of Electrical and Computer Engineering Frost Institute for Data Science and Computing Coral Gables33146 United States University of Miami Department of Industrial and Systems Engineering Coral Gables33146 United States Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China North Carolina State University Department of Computer Science RaleighNC27695 United States Beijing Key Laboratory of Network System Architecture and Convergence China Beijing University of Posts and Telecommunications Beijing Advanced Information Network Laboratory Beijing100876 China

This article investigates the adaptive resource allocation scheme for digital twin (DT) synchronization optimization over dynamic wireless networks. In our considered model, a base station (BS) continuously collects factory physical object state data from wireless devices to build a real-time virtual DT system for factory event analysis. Due to continuous data transmission, maintaining DT synchronization must use extensive wireless resources. To address this issue, a subset of devices is selected to transmit their sensing data, and resource block (RB) allocation is optimized. This problem is formulated as a constrained Markov process (CMDP) problem that minimizes the long-term mismatch between the physical and virtual systems. To solve this CMDP, we first transform the problem into a dual problem that refines RB constraint impacts on device scheduling strategies. We then propose a continual reinforcement learning (CRL) algorithm to solve the dual problem. The CRL algorithm learns a stable policy across historical experiences for quick adaptation to dynamics in physical states and network capacity. Simulation results show that the CRL can adapt quickly to network capacity changes and reduce normalized root mean square error (NRMSE) between physical and virtual states by up to 55.2%, using the same RB number as traditional methods. © 2025 IEEE. All rights reserved.

关键词： Markov processes

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Downlink Transmit-End Beam Refinement for mmWave Communications Under Mobility

Downlink Transmit-End Beam Refinement for mmWave Communicati...

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2023 International Conference on Electrical engineering and Photonics, EExPolytech 2023

作者： Fokin, Grigoriy Grishin, Ilya Okuneva, Darina The Bonch-Bruevich Saint Petersburg State University of Telecommunications Laboratory of Software Defined Radio Saint Petersburg Russia The Bonch-Bruevich Saint Petersburg State University of Telecommunications Department of Communication Networks and Data Transmission Saint Petersburg Russia The Bonch-Bruevich Saint Petersburg State University of Telecommunications Department of Software Engineering and Computer Facilities Saint Petersburg Russia

ISBN: (纸本)9798350310481

This article discusses a method for adjusting the radiation pattern of a base station antenna array when conducting radio communications in the millimeter wavelength range for mobile user devices. The article describes a technique for selecting a training sequence of beams that minimizes the Cramer-Rao lower bound when estimating the transmission direction. The proposed technique makes it possible to reduce the beam adjustment time for transmission by 16 times compared to the conventional protocol, which improves the quality of service for highly mobile users. © 2023 IEEE.

关键词： Beamforming

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Quantitative Applications of Weather Satellite data for Nowcasting:Progress and Challenges

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Journal of Meteorological Research 2024年第3期38卷 399-413页

作者： Jun LI Jing ZHENG Bo LI Min MIN Yanan LIU Chian-Yi LIU Zhenglong LI WPaul MENZEL Timothy J.SCHMIT John L.CINTINEO Scott LINDSTROM Scott BACHMEIER Yunheng XUE Yayu MA Di DI Han LIN Innovation Centre for Fengyun Meteorological Satellite(FYSIC) National Satellite Meteorological CentreChina Meteorological AdministrationBeijing100081China School of Atmospheric Sciences and Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies Sun Yat-sen University and Southern Laboratory of Ocean Science and EngineeringZhuhai519082China Key Laboratory of Geographic Information Science(Ministry of Education) East China Normal UniversityShanghai200241China Research Center for Environmental Changes Academia SinicaTaipei11529China Cooperative Institute for Meteorological Satellite Studies University of Wisconsin-MadisonMadisonWI53706USA Sensors and Calibration Branch STAR/NESDISMadisonWI53706USA Wuxi University Wuxi214105China School of Computer Science Chengdu University of Information TechnologyChengdu610225China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science&TechnologyNanjing210044China Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education National and Local Joint Engineering Research Center of Satellite Geospatial Information TechnologyFuzhou UniversityFuzhou350108China

Monitoring and predicting highly localized weather events over a very short-term period,typically ranging from minutes to a few hours,are very important for decision makers and public *** these events usually relies on radar observations through monitoring and *** advanced high-resolution imaging and sounding observations from weather satellites,nowcasting can be enhanced by combining radar,satellite,and other data,while quantitative applications of those data for nowcasting are advanced through using machine learning *** applications include monitoring the location,impact area,intensity,water vapor,atmospheric instability,precipitation,physical properties,and optical properties of the severe storm at different stages(pre-convection,initiation,development,and decaying),identification of storm types(wind,snow,hail,etc.),and predicting the occurrence and evolution of the *** observations can provide information on the environmental characteristics in the preconvection stage and are very useful for situational awareness and storm *** paper provides an overview of recent progress on quantitative applications of satellite data in nowcasting and its challenges,and future perspectives are also addressed and discussed.

关键词： weather satellite quantitative applications nowcasting pre-convection

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Load balance and time delay efficient algorithm for VNF service chain deployment based on DQN 18

Load balance and time delay efficient algorithm for VNF serv...

引用

18th International Conference on Computational Intelligence and Security, CIS 2022

作者： Xuan, Hejun Lin, Lidan Liu, Zhenghui Zhao, Xuelin Xinyang Normal University Department of Computer and Information Technology China Big Data Xinyang Normal University Henan Key Laboratory of Analysis and Applications of Education Xinyang Henan China Luo He Vocational Technology College Department of Information Engineering Luohe Henan China

ISBN: (纸本)9798350346275

In mobile edge computing, computing and storage resources are close to the network of the user device, which can effectively reduce network access and computing service delay. However, network function virtualization for mobile edge computing networks is more challenging due to the strong coupling of CPU resources, storage resources, and wireless resources. In order to solve the problems of load balance and long response time of user-oriented service function chain deployment algorithm in mobile edge computing networks, this paper proposed a load balance and time delay efficient algorithm (denoted as LBDQN) for virtual network function service chain deployment problem based Deep Q-LearningFirst, a global optimization model, which minimizes time delay and maximizes the load balance, is established. Then, a new real-time algorithm for VNF service chain deployment based on DQN is proposed. In this algorithm, an adaptive ϵ-greedy method is designed. In addition, a particle swarm optimization is used to optimize the neural network parameters. To demonstrate the efficiency of the proposed algorithm, some simulation experiments are conducted and the experimental results show that the algorithm can effectively reduce the time delay and improve the load balance than the compared algorithms. © 2022 IEEE.

关键词： Time delay

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A General Albedo Recovery Approach for Aerial Photogrammetric Images through Inverse Rendering

arXiv

引用

arXiv 2024年

作者： Song, Shuang Qin, Rongjun Geospatial Data Analytics Laboratory The Ohio State University Columbus United States Department of Civil Environmental and Geodetic Engineering The Ohio State University Columbus United States Department of Electrical and Computer Engineering The Ohio State University Columbus United States Translational Data Analytics Institute The Ohio State University Columbus United States

Modeling outdoor scenes for the synthetic 3D environment requires the recovery of reflectance/albedo information from raw images, which is an ill-posed problem due to the complicated unmodeled physics in this process (e.g., indirect lighting, volume scattering, specular reflection). The problem remains unsolved in a practical context. The recovered albedo can facilitate model relighting and shading, which can further enhance the realism of rendered models and the applications of digital twins. Typically, photogrammetric 3D models simply take the source images as texture materials, which inherently embed unwanted lighting artifacts (at the time of capture) into the texture. Therefore, these "polluted" textures are suboptimal for a synthetic environment to enable realistic rendering. In addition, these embedded environmental lightings further bring challenges to photo-consistencies across different images that cause image-matching uncertainties. This paper presents a general image formation model for albedo recovery from typical aerial photogrammetric images under natural illuminations and derives the inverse model to resolve the albedo information through inverse rendering intrinsic image decomposition. Our approach builds on the fact that both the sun illumination and scene geometry are estimable in aerial photogrammetry, thus they can provide direct inputs for this ill-posed problem. This physics-based approach does not require additional input other than data acquired through the typical drone-based photogrammetric collection and was shown to favorably outperform existing approaches. We also demonstrate that the recovered albedo image can in turn improve typical image processing tasks in photogrammetry such as feature and dense matching, edge, and line extraction. [This work extends our prior work "A Novel Intrinsic Image Decomposition Method to Recover Albedo for Aerial Images in Photogrammetry Processing" in ISPRS Congress 2022]. The code will be made available

关键词： Inverse problems

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Unveiling Vulnerability of Self-Attention

arXiv

引用

arXiv 2024年

作者： Liong, Khai Jiet Wu, Hongqiu Zhao, Hai Xiaoshan, Li Minjie, Bian Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China Shanghai Technology Innovation Department Shanghai Data Group Co. Ltd China Shanghai Data Group Co. Ltd China

Pre-trained language models (PLMs) are shown to be vulnerable to minor word changes, which poses a big threat to real-world systems. While previous studies directly focus on manipulating word inputs, they are limited by their means of generating adversarial samples, lacking generalization to versatile real-world attack. This paper studies the basic structure of transformer-based PLMs, the self-attention (SA) mechanism. (1) We propose a powerful perturbation technique HackAttend, which perturbs the attention scores within the SA matrices via meticulously crafted attention masks. We show that state-of-the-art PLMs fall into heavy vulnerability that minor attention perturbations (1%) can produce a very high attack success rate (98%). Our paper expands the conventional text attack of word perturbations to more general structural perturbations. (2) We introduce S-Attend, a novel smoothing technique that effectively makes SA robust via structural perturbations. We empirically demonstrate that this simple yet effective technique achieves robust performance on par with adversarial training when facing various text attackers. Code is publicly available at ***/liongkj/HackAttend. Copyright © 2024, The Authors. All rights reserved.

关键词： Semantics

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Towards Intelligent Transportation with Pedestrians and Vehicles In-the-Loop: A Surveillance Video-Assisted Federated Digital Twin Framework

arXiv

引用

arXiv 2025年

作者： Li, Xiaolong Wei, Jianhao Wang, Haidong Dong, Li Chen, Ruoyang Yi, Changyan Cai, Jun Niyato, Dusit Shen, Xuemin The Xiangjiang Laboratory Hunan Provincial General University Key Laboratory of IoT Intelligent Sensing and Distributed Collaborative Optimization Hunan University of Technology and Business Changsha410205 China The College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics China The Department of Electrical and Computer Engineering University of Concordia Montreal Canada The College of Computing and Data Science Nanyang Technological University Singapore The Department of Electrical and Computer Engineering University of Waterloo Canada

In intelligent transportation systems (ITSs), incorporating pedestrians and vehicles in-the-loop is crucial for developing realistic and safe traffic management solutions. However, there is falls short of simulating complex real-world ITS scenarios, primarily due to the lack of a digital twin implementation framework for characterizing interactions between pedestrians and vehicles at different locations in different traffic environments. In this article, we propose a surveillance video assisted federated digital twin (SV-FDT) framework to empower ITSs with pedestrians and vehicles in-the-loop. Specifically, SVFDT builds comprehensive pedestrian-vehicle interaction models by leveraging multi-source traffic surveillance videos. Its architecture consists of three layers: (i) the end layer, which collects traffic surveillance videos from multiple sources;(ii) the edge layer, responsible for semantic segmentation-based visual understanding, twin agent-based interaction modeling, and local digital twin system (LDTS) creation in local regions;and (iii) the cloud layer, which integrates LDTSs across different regions to construct a global DT model in realtime. We analyze key design requirements and challenges and present core guidelines for SVFDT’s system implementation. A testbed evaluation demonstrates its effectiveness in optimizing traffic management. Comparisons with traditional terminal-server frameworks highlight SV-FDT’s advantages in mirroring delays, recognition accuracy, and subjective evaluation. Finally, we identify some open challenges and discuss future research directions. Copyright © 2025, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Dynamic Graph Neural Networks for Joint Terahertz based Sensing and Communication Optimization in Vehicular Networks

Dynamic Graph Neural Networks for Joint Terahertz based Sens...

引用

IEEE Conference on Wireless Communications and Networking

作者： Xuefei Li Mingzhe Chen Ye Hu Zhilong Zhang Danpu Liu Shiwen Mao Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijina China Department-of Electrical and Computer Engineering and Institute for Data Science and Computing University of Miami Coral Gables FL USA Department of Industrial and System Engineering University of Miami Coral Gables FL USA Department of Electrical and Computer Engineering Auburn University Auburn AL USA

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

In this paper, the problem of vehicle service mode selection (sensing, communication, or both) and vehicle connections within terahertz (THz) enabled joint sensing and communications over vehicular networks is studied. The considered network consists of several service provider vehicles (SPVs) that can provide: 1) only sensing service, 2) only communication service, and 3) both services, sensing service request vehicles, and communication service request vehicles. Based on the vehicle network topology and their service accessibility, SPVs strategically select service request vehicles to provide sensing, communication, or both services. This problem is formulated as an optimization problem, aiming to maximize the number of successfully served vehicles by jointly determining the service mode of each SPV and its associated vehicles. To solve this problem, we propose a dynamic graph neural network (GNN) model that selects appropriate graph information aggregation functions according to the vehicle network topology, thus extracting more vehicle network information compared to traditional static GNNs that use fixed aggregation functions for different vehicle network topologies. Using the extracted vehicle network information, the service mode of each SPV and its served service request vehicles will be determined. Simulation results show that the proposed dynamic GNN based scheme can improve the number of successfully served vehicles by up to 17% compared to a GNN based algorithm with a fixed neural network model.

关键词： Network topology Simulation Heuristic algorithms Graph neural networks Sensors data mining Vehicle dynamics

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A Bi-objective Optimal Scheme for 5G Base Station Deployment Based on BPSO 12th

A Bi-objective Optimal Scheme for 5G Base Station Deployment...

引用

12th International Conference on computer engineering and Networks, CENet 2022

作者： Zhu, Tao Xu, Yin-qing Guo, Hao-qi Wang, Yi-bo Department of Computer Information and Cyber Security Jiangsu Police Institute Nanjing China Engineering Research Center of Electronic Data Forensics Analysis Jiangsu Province Nanjing China Key Laboratory of Digital Forensics Department of Public Security of Jiangsu Province Nanjing210031 China

ISBN: (纸本)9789811969003

The 5G mobile network is a kind of critical information infrastructure for future Internet of Things. Due to its rapid development, the planning and deployment of 5G network base stations is a more urgent and meaningful problem than ever before from the aspect of optimization. Because the purpose of establishing a 5G base station is to make its wireless signal cover as many areas as possible, a 0–1 programming model with two optimal objectives is proposed for 5G base stations based on the cover set. Then after analyzing the difficulties in solving the problem expressed by above model, employing the idea of divide and conquer and the strategies of parallelization, a scheme based on Binary Particle Swarm Optimization (BPSO) algorithm is proposed to solve this problem. In the first step of the scheme, the partition processing based on coordinate position is considered by the way of dividing the target area into many smaller sub-areas with the algorithm of Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH). The next step is to use BPSO algorithm improved by sparse particles initialization and a suppressor factor to solve each small sub-area with the parallel computing and the memory mapping technology. The proposed approach has been tested in several experiments and the experimental results demonstrate its effectiveness. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Base stations

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