International Journal of Network Dynamics and Intelligence最新文献_第2页

On the Formal Evaluation of the Robustness of Neural Networks and Its Pivotal Relevance for AI-Based Safety-Critical Domains 论神经网络鲁棒性的形式评估及其对基于人工智能的安全关键领域的重要意义

International Journal of Network Dynamics and Intelligence Pub Date : 2023-12-21 DOI: 10.53941/ijndi.2023.100018

Mohamed Ibn Khedher, Houda Jmila, Mounim A. El-Yacoubi

{"title":"On the Formal Evaluation of the Robustness of Neural Networks and Its Pivotal Relevance for AI-Based Safety-Critical Domains","authors":"Mohamed Ibn Khedher, Houda Jmila, Mounim A. El-Yacoubi","doi":"10.53941/ijndi.2023.100018","DOIUrl":"https://doi.org/10.53941/ijndi.2023.100018","url":null,"abstract":"Survey/Review Study\u0000On the Formal Evaluation of the Robustness of Neural Networks and Its Pivotal Relevance for AI-Based Safety-Critical Domains\u0000\u0000Mohamed Ibn Khedher 1,*, Houda Jmila 2, and Mounim A. El-Yacoubi 2\u0000\u0000\u00001 IRT-SystemX, 2 Bd Thomas Gobert, Palaiseau 91120, France\u00002 Samovar, Telecom SudParis, Institut Polytechnique de Paris, 19 place Marguerite Perey, Palaiseau 91120, France\u0000* Correspondence: ibnkhedhermohamed@hotmail.com\u0000 \u0000 \u0000Received: 11 July 2023\u0000Accepted: 31 October 2023\u0000Published: 21 December 2023\u0000 \u0000\u0000Abstract: Neural networks serve as a crucial role in critical tasks, where erroneous outputs can have severe consequences. Traditionally, the validation of neural networks has focused on evaluating their performance across a large set of input points to ensure desired outputs. However, due to the virtually infinite cardinality of the input space, it becomes impractical to exhaustively check all possible inputs. Networks exhibiting strong performance on extensive input samples may fail to generalize correctly in novel scenarios, and remain vulnerable to adversarial attacks. This paper presents the general pipeline of neural network robustness and provides an overview of different domains that work together to achieve robustness guarantees. These domains include evaluating the robustness against adversarial attacks, evaluating the robustness formally and applying defense techniques to enhance the robustness when the model is compromised.","PeriodicalId":183984,"journal":{"name":"International Journal of Network Dynamics and Intelligence","volume":"32 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138949668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FSS-Net: A Fast Search Structure for 3D Point Clouds in Deep Learning FSS-Net:深度学习中三维点云的快速搜索结构

International Journal of Network Dynamics and Intelligence Pub Date : 2023-06-12 DOI: 10.53941/ijndi.2023.100005

Jiawei Wang, Yan Zhuang, Yisha Liu

{"title":"FSS-Net: A Fast Search Structure for 3D Point Clouds in Deep Learning","authors":"Jiawei Wang, Yan Zhuang, Yisha Liu","doi":"10.53941/ijndi.2023.100005","DOIUrl":"https://doi.org/10.53941/ijndi.2023.100005","url":null,"abstract":"Article\u0000FSS-Net: A Fast Search Structure for 3D Point Clouds in Deep Learning\u0000\u0000Jiawei Wang 1, Yan Zhuang 1,*, and Yisha Liu 2,*\u0000\u0000\u00001 School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China\u00002 Information Science and Technology College, Dalian Maritime University, Dalian 116026, China\u0000* Correspondence: zhuang@dlut.edu.cn; liuyisha@dlmu.edu.cn\u0000 \u0000 \u0000Received: 5 April 2023\u0000Accepted: 5 May 2023\u0000 \u0000\u0000Abstract: The deep learning methods achieve good results in the semantic segmentation and classification of the 3D point clouds. The popular convolutional neural networks illustrate the importance of using the neighboring information of the points. Searching the neighboring points is an important process that can get the context information of each point. The K-nearest neighbor (KNN) search and ball query methods are usually used to find the neighboring points, but a long time is required to construct the KD-tree and calculate the Euclidean distance. In this work, we introduce a fast approach (called the voxel search) to finding the neighbors, where the key is to use the voxel coordinates to search the neighbors directly. However, it is difficult to apply this method directly to the general network structure such as the U-net. In order to improve its applicability, the corresponding up-sampling and down-sampling methods are proposed. Additionally, we propose a fast search structure network (FSS-net) which consists of the feature extraction layer and the sampling layer. In order to demonstrate the effectiveness of the FSS-net, we conduct experiments on a single object in both indoor and outdoor environments. The speed of the voxel search approach is compared with that of the KNN and ball query. The experimental results show that our method is faster and can be directly applied to any point-based deep learning networks.","PeriodicalId":183984,"journal":{"name":"International Journal of Network Dynamics and Intelligence","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124090276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Novel Multi-Objective Optimization Approach with Flexible Operation Planning Strategy for Truck Scheduling 基于柔性作业规划策略的货车调度多目标优化方法

International Journal of Network Dynamics and Intelligence Pub Date : 2023-06-12 DOI: 10.53941/ijndi.2023.100002

Yiming Wang, Weibo Liu, Chuan-Chao Wang, F. Fadzil, S. Lauria, Xiaohui Liu

{"title":"A Novel Multi-Objective Optimization Approach with Flexible Operation Planning Strategy for Truck Scheduling","authors":"Yiming Wang, Weibo Liu, Chuan-Chao Wang, F. Fadzil, S. Lauria, Xiaohui Liu","doi":"10.53941/ijndi.2023.100002","DOIUrl":"https://doi.org/10.53941/ijndi.2023.100002","url":null,"abstract":"Article\u0000A Novel Multi-Objective Optimization Approach with Flexible Operation Planning Strategy for Truck Scheduling\u0000\u0000Yiming Wang , Weibo Liu *, Chuang Wang , Futra Fadzil , Stanislao Lauria , and Xiaohui Liu\u0000\u0000\u0000Department of Computer Science, Brunel University London, Uxbridge, Middlesex, UB8 3PH, United Kingdom\u0000* Correspondence: Weibo.Liu2@brunel.ac.uk\u0000 \u0000 \u0000Received: 13 April 2023\u0000Accepted: 25 April 2023\u0000 \u0000\u0000Abstract: The transportation system plays an important role in the open-pit mine. As an effective solution, smart scheduling has been widely investigated to manage transportation operations and increase transportation capabilities. Some existing truck scheduling methods tend to treat the critical parameter (i.e., the moving speed of the truck) as a constant, which is impractical in real-world industrial scenarios. In this paper, a multi-objective optimization (MOO) algorithm is proposed for truck scheduling by considering three objectives, i.e., minimizing the queuing time, maximizing the productivity, and minimizing the financial cost. Specifically, the proposed algorithm is employed to search continuously in the solution space, where the truck moving speed and truck payload are chosen as the operational variables. Moreover, a smart scheduling application integrating the proposed MOO algorithm is developed to assist the user in selecting a suitable scheduling plan. Experimental results demonstrate that our proposed MOO approach is effective in tackling the truck scheduling problem, which could satisfy a wide range of transportation conditions and provide managers with flexible scheduling options.","PeriodicalId":183984,"journal":{"name":"International Journal of Network Dynamics and Intelligence","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125698505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Unsupervised Spectral Analysis of Bio-Dyed Textile Samples 生物染色纺织品样品的无监督光谱分析

International Journal of Network Dynamics and Intelligence Pub Date : 2023-06-12 DOI: 10.53941/ijndi.2023.100001

Zong-Yue Li, J. Hyttinen, R. Räisänen, Xiao-Zhi Gao, M. Hauta-Kasari

{"title":"Unsupervised Spectral Analysis of Bio-Dyed Textile Samples","authors":"Zong-Yue Li, J. Hyttinen, R. Räisänen, Xiao-Zhi Gao, M. Hauta-Kasari","doi":"10.53941/ijndi.2023.100001","DOIUrl":"https://doi.org/10.53941/ijndi.2023.100001","url":null,"abstract":"Article\u0000Unsupervised Spectral Analysis of Bio-Dyed Textile Samples\u0000\u0000Zong-Yue Li 1,*, Joni Hyttinen 1, Riikka Räisänen 2, Xiao-Zhi Gao 1, and Markku Hauta-Kasari 1\u0000\u0000\u00001 School of Computing, Faculty of Science, Forestry and Technology, University of Eastern Finland, Joensuu, 80101, Kuopio, 70211, Finland\u00002 Department of Education, Faculty of Educational Sciences, University of Helsinki, Helsinki, 00014 , Finland\u0000* Correspondence: winstonli711@gmail.com\u0000 \u0000 \u0000Received: 12 March 2023\u0000Accepted: 23 March 2023\u0000 \u0000\u0000Abstract: Natural compounds such as biological colorants (biocolorants) have long been employed as crucial ingredients for dying textile in the textile industry. As one part of the BioColour Consortium project, our goal is to take advantage of machine learning (in cluster analysis) to discover possible clusters of bio-dyed textile in the absence of ground truth labels or other knowledge of expert domains. Specifically, we use unsupervised learning methods of agglomerative clustering, fuzzy c-means, ordering points to identify the clustering structure (OPTICS) and self-organizing maps (SOMs), resulting in an investigation that combines data visualization and cluster analysis. In summary, we apply some selected data mining methods to 1) discover hidden clusters emerging among products that are colored with biocolorant (specifically bio-dyed textile samples), and 2) show the potentials of clustering techniques in the case study.","PeriodicalId":183984,"journal":{"name":"International Journal of Network Dynamics and Intelligence","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115271162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Survey on Recent Advances in Distributed Filtering over Sensor Networks Subject to Communication Constraints 受通信约束的传感器网络分布式滤波研究进展综述

International Journal of Network Dynamics and Intelligence Pub Date : 2023-06-12 DOI: 10.53941/ijndi0201007

Yu-Ang Wang, Bo Shen, Lei Zou, Qing‐Long Han

{"title":"A Survey on Recent Advances in Distributed Filtering over Sensor Networks Subject to Communication Constraints","authors":"Yu-Ang Wang, Bo Shen, Lei Zou, Qing‐Long Han","doi":"10.53941/ijndi0201007","DOIUrl":"https://doi.org/10.53941/ijndi0201007","url":null,"abstract":"Survey/review study\u0000A Survey on Recent Advances in Distributed Filtering over Sensor Networks Subject to Communication Constraints\u0000\u0000Yu-Ang Wang 1,2, Bo Shen 1,2, Lei Zou 1,2, and Qing-Long Han 3,*\u0000\u0000\u00001 College of Information Science and Technology, Donghua University, Shanghai 201620, China\u00002 Engineering Research Center of Digitalized Textile and Fashion Technology, Ministry of Education, Shanghai 201620, China\u00003 School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Melbourne, VIC 3122, Australia\u0000* Correspondence: qhan@swin.edu.au\u0000 \u0000 \u0000Received: 30 January 2023\u0000Accepted: 31 January 2023\u0000Published: \u0000 \u0000\u0000Abstract: The sensor network (SN) has long been an ongoing research topic with many successful applications in a wide range of fields. Lying in the core part of this paper is the distributed filtering problem over SNs that has been gaining growing research interests. We aim to provide a timely survey on recent advances in the distributed filtering problems over SNs subject to communication constraints. First, some basic knowledge concerning the distributed filter design issue is provided in terms of background introduction and mathematical descriptions. Then, some frequently encountered network-induced complexities resulting from communication constraints are comprehensively reviewed. Subsequently, the latest research progress of the distributed filtering schemes is discussed in detail for various systems over SNs with different performance specifications. Furthermore, practical applications of the distributed filtering methods are presented that include target tracking and distributed generation. Finally, concluding remarks are given followed by possible future research directions.","PeriodicalId":183984,"journal":{"name":"International Journal of Network Dynamics and Intelligence","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122680513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Background Replacement in Video Conferencing 视频会议中的背景替换

International Journal of Network Dynamics and Intelligence Pub Date : 2023-06-12 DOI: 10.53941/ijndi.2023.100004

K. Shahi., Yongmin Li

{"title":"Background Replacement in Video Conferencing","authors":"K. Shahi., Yongmin Li","doi":"10.53941/ijndi.2023.100004","DOIUrl":"https://doi.org/10.53941/ijndi.2023.100004","url":null,"abstract":"Article\u0000Background Replacement in Video Conferencing\u0000\u0000Kiran Shahi *, and Yongmin Li\u0000\u0000\u00001 Department of Computer Science, Brunel University London, Uxbridge, UB8 3PH, United Kingdom\u0000* Correspondence: 2144420@alumni.brunel.ac.uk\u0000 \u0000 \u0000Received: 17 March 2023\u0000Accepted: 24 April 2023\u0000 \u0000\u0000Abstract: Background replacement is one of the most used features in video conferencing applications by many people, perhaps mainly for privacy protection, but also for other purposes such as branding, marketing and promoting professionalism. However, the existing applications in video conference tools have serious limitations. Most applications tend to generate strong artefacts (while there is a slight change in the perspective of the background), or require green screens to avoid such artefacts, which results in an unnatural background or even exposes the original background to other users in the video conference. In this work, we aim to study the relationship between the foreground and background in real-time videos. Three different methods are presented and evaluated, including the baseline U-Net, the lightweight U-Net MobileNet, and the U-Net MobileNet&ConvLSTM models. The above models are trained on public datasets for image segmentation. Experimental results show that both the lightweight U-Net MobileNet and the U-Net MobileNet& ConvLSTM models achieve superior performance as compared to the baseline U-Net model.","PeriodicalId":183984,"journal":{"name":"International Journal of Network Dynamics and Intelligence","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131286509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Is High-Fidelity Important for Human-like Virtual Avatars in Human Computer Interactions? 在人机交互中，高保真度对类人虚拟化身很重要吗?

International Journal of Network Dynamics and Intelligence Pub Date : 2023-03-27 DOI: 10.53941/ijndi0201008

Qiongdan Cao, Hui Yu, Paul Charisse, Si Qiao, B. Stevens

{"title":"Is High-Fidelity Important for Human-like Virtual Avatars in Human Computer Interactions?","authors":"Qiongdan Cao, Hui Yu, Paul Charisse, Si Qiao, B. Stevens","doi":"10.53941/ijndi0201008","DOIUrl":"https://doi.org/10.53941/ijndi0201008","url":null,"abstract":"Survey/review study\u0000Is High-Fidelity Important for Human-like Virtual Avatars in Human Computer Interactions?\u0000\u0000Qiongdan Cao , Hui Yu ,*, Paul Charisse , Si Qiao , and Brett Stevens\u0000\u0000\u00001 University of Portsmouth, Portsmouth, PO1 2UP, UK\u0000* Correspondence: hui.yu@port.ac.uk\u0000 \u0000 \u0000Received: 2 March 2023\u0000Accepted: 6 March 2023\u0000Published: 27 March 2023\u0000 \u0000\u0000Abstract: As virtual avatars have become increasingly popular in recent years, current needs indicate that “interactivity” is crucial for inducing a positive response from users towards these avatars, especially in human computer interactions (HCI). This paper reviews recent works on high-fidelity human-like virtual avatars (e.g. high visual and motion fidelity) and discusses the critical question——“Is high-fidelity a positive choice for virtual avatars to achieve better interactions in HCI”. Furthermore, we summarise current technical approaches to developing those virtual avatars. We investigate the advantages and disadvantages of high-fidelity virtual avatars in different areas focusing on addressing the effect of motion, especially the upper body. Research shows that high-fidelity is a positive choice for virtual avatars, although it may depend on the application.","PeriodicalId":183984,"journal":{"name":"International Journal of Network Dynamics and Intelligence","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130565026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Reinforcement Learning for Selective Disassembly System Optimization Problems: A Survey 选择性拆卸系统优化问题的强化学习研究

International Journal of Network Dynamics and Intelligence Pub Date : 2023-02-23 DOI: 10.53941/ijndi0201001

Xiwang Guo, Zhiliang Bi, Jiacun Wang, Shujin Qin, Shixin Liu, Liang Qi

{"title":"Reinforcement Learning for Selective Disassembly System Optimization Problems: A Survey","authors":"Xiwang Guo, Zhiliang Bi, Jiacun Wang, Shujin Qin, Shixin Liu, Liang Qi","doi":"10.53941/ijndi0201001","DOIUrl":"https://doi.org/10.53941/ijndi0201001","url":null,"abstract":"Survey/review study\u0000Reinforcement Learning for Disassembly System Optimization Problems: A Survey\u0000\u0000Xiwang Guo 1,2,*, Zhiliang Bi 2, Jiacun Wang 1, Shujin Qin 3, Shixin Liu 4, and Liang Qi 5\u0000\u0000\u00001 Department of Computer Science and Software Engineering, Monmouth University, New Jersey 07710, USA\u00002 Department of Information Control, Liaoning Petrochemical University, Fushun 113005, China\u00003 Department of Economic Management, Shangqiu Normal University, Shangqiu 476000, China\u00004 Department of Information Science and Engineering, Northeast University, Shenyang 110819, China\u00005 Department of Computer Intelligence Science and Technology, Shandong University of Science and Technology, Qingdao 266590, China\u0000* Correspondence: x.w.guo@163.com\u0000 \u0000 \u0000Received: 16 October 2022\u0000Accepted: 28 November 2022\u0000Published: \u0000 \u0000\u0000Abstract: The disassembly complexity of end-of-life products increases continuously. Traditional methods are facing difficulties in solving the decision-making and control problems of disassembly operations. On the other hand, the latest development in reinforcement learning makes it more feasible to solve such kind of complex problems. Inspired by behaviorism psychology, reinforcement learning is considered as one of the most promising directions to achieve universal artificial intelligence (AI). In this context, we first review the basic ideas, mathematical models, and various algorithms of reinforcement learning. Then, we introduce the research progress and application subjects in the field of disassembly and recycling, such as disassembly sequencing, disassembly line balancing, product transportation, disassembly layout, etc. In addition, the prospects, challenges and applications of reinforcement learning based disassembly and recycling are also comprehensively analyzed and discussed.","PeriodicalId":183984,"journal":{"name":"International Journal of Network Dynamics and Intelligence","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132856239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Deep Learning Attention Mechanism in Medical Image Analysis: Basics and Beyonds 医学图像分析中的深度学习注意机制:基础与超越

International Journal of Network Dynamics and Intelligence Pub Date : 2023-02-23 DOI: 10.53941/ijndi0201006

Xiang Li, Minglei Li, Pengfei Yan, Guanyi Li, Yuchen Jiang, Hao Luo, Shen Yin

{"title":"Deep Learning Attention Mechanism in Medical Image Analysis: Basics and Beyonds","authors":"Xiang Li, Minglei Li, Pengfei Yan, Guanyi Li, Yuchen Jiang, Hao Luo, Shen Yin","doi":"10.53941/ijndi0201006","DOIUrl":"https://doi.org/10.53941/ijndi0201006","url":null,"abstract":"Survey/review study\u0000Deep Learning Attention Mechanism in Medical Image Analysis: Basics and Beyonds\u0000\u0000Xiang Li 1, Minglei Li 1, Pengfei Yan 1, Guanyi Li 1, Yuchen Jiang 1, Hao Luo 1,*, and Shen Yin 2\u0000\u0000\u00001 Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, China\u00002 Department of Mechanical and Industrial Engineering, Faculty of Engineering, Norwegian University of Science and Technology, Trondheim 7034, Norway\u0000* Correspondence: hao.luo@hit.edu.cn\u0000 \u0000 \u0000Received: 16 October 2022\u0000Accepted: 25 November 2022\u0000Published: \u0000 \u0000\u0000Abstract: With the improvement of hardware computing power and the development of deep learning algorithms, a revolution of \"artificial intelligence (AI) + medical image\" is taking place. Benefiting from diversified modern medical measurement equipment, a large number of medical images will be produced in the clinical process. These images improve the diagnostic accuracy of doctors, but also increase the labor burden of doctors. Deep learning technology is expected to realize an auxiliary diagnosis and improve diagnostic efficiency. At present, the method of deep learning technology combined with attention mechanism is a research hotspot and has achieved state-of-the-art results in many medical image tasks. This paper reviews the deep learning attention methods in medical image analysis. A comprehensive literature survey is first conducted to analyze the keywords and literature. Then, we introduce the development and technical characteristics of the attention mechanism. For its application in medical image analysis, we summarize the related methods in medical image classification, segmentation, detection, and enhancement. The remaining challenges, potential solutions, and future research directions are also discussed.","PeriodicalId":183984,"journal":{"name":"International Journal of Network Dynamics and Intelligence","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122314475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

A Survey of Algorithms, Applications and Trends for Particle Swarm Optimization 粒子群优化算法、应用及发展趋势综述

International Journal of Network Dynamics and Intelligence Pub Date : 2023-02-23 DOI: 10.53941/ijndi0201002

Jingzhong Fang, Weibo Liu, Linwei Chen, S. Lauria, Alina Miron, Xiaohui Liu

{"title":"A Survey of Algorithms, Applications and Trends for Particle Swarm Optimization","authors":"Jingzhong Fang, Weibo Liu, Linwei Chen, S. Lauria, Alina Miron, Xiaohui Liu","doi":"10.53941/ijndi0201002","DOIUrl":"https://doi.org/10.53941/ijndi0201002","url":null,"abstract":"Survey/review study\u0000A Survey of Algorithms, Applications and Trends for Particle Swarm Optimization\u0000\u0000Jingzhong Fang 1, Weibo Liu 1,*, Linwei Chen 2, Stanislao Lauria 1, Alina Miron 1, and Xiaohui Liu 1\u0000\u0000\u00001 Department of Computer Science, Brunel University London, Uxbridge, Middlesex, UB8 3PH, United Kingdom\u00002 The School of Engineering, University of Warwick, Coventry CV4 7AL, United Kingdom\u0000* Correspondence: Weibo.Liu2@brunel.ac.uk\u0000 \u0000 \u0000Received: 18 October 2022\u0000Accepted: 28 November 2022\u0000Published: \u0000 \u0000\u0000Abstract: Particle swarm optimization (PSO) is a popular heuristic method, which is capable of effectively dealing with various optimization problems. A detailed overview of the original PSO and some PSO variant algorithms is presented in this paper. An up-to-date review is provided on the development of PSO variants, which include four types i.e., the adjustment of control parameters, the newly-designed updating strategies, the topological structures, and the hybridization with other optimization algorithms. A general overview of some selected applications (e.g., robotics, energy systems, power systems, and data analytics) of the PSO algorithms is also given. In this paper, some possible future research topics of the PSO algorithms are also introduced.","PeriodicalId":183984,"journal":{"name":"International Journal of Network Dynamics and Intelligence","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121406850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10