检索结果-内蒙古大学图书馆

6th International Symposium on computer, Consumer and Control, IS3C 2023

作者： Zhang, Junbin Tsai, Pei-Hsuan Tsai, Meng-Hsun National Cheng Kung University Department of Computer Science and Information Engineering Tainan Taiwan National Cheng Kung University Institute of Manufacturing Information and Systems Tainan Taiwan National Yang Ming Chiao Tung University Department of Computer Science Hsinchu Taiwan

ISBN: (纸本)9798350301953

In real-world interactive applications, where videos are generated in real-time and require immediate feedback, online segmentation has practical advantages over offline inference. Many excellent previous models have been developed for offline scenarios, while real-time prediction for temporal action segmentation (TAS) is a difficult task. Some interactive applications can tolerate a certain amount of delay. In this paper, we propose a node delay embedding of a dynamic graph for real-time TAS. We transform the video stream into a dynamic graph stream that evolves over time. We define past, current, and future nodes to construct sub-graphs at each step. Specifically, future nodes are sampled using our proposed node delay method. A graph model is utilized to aggregate past, current, and future node information to update the representation of current nodes and predict their labels. To the best of our knowledge, it is the first real-time TAS graph model with delay embedding. Experiments show that delay embedding enhances node representation and improves performance. Overall, our proposed approach provides a promising solution for real-time TAS. © 2023 IEEE.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

Exact Output Synchronization of Discrete-Time Multi-Agent systems in the Presence of Disturbances and Measurement Noise with Known Frequencies via Scale-Free Protocol Design 42

Exact Output Synchronization of Discrete-Time Multi-Agent Sy...

引用

42nd Chinese Control Conference, CCC 2023

作者： Liu, Zhenwei Zhang, Meirong Saberi, Ali Stoorvogel, Anton A. College of Information Science and Engineering Northeastern University Shenyang110819 China School of Engineering and Applied Science Gonzaga University SpokaneWA United States School of Electrical Engineering and Computer Science Washington State University PullmanWA99164 United States Mathematics and Computer Science Department of Electrical Engineering University of Twente Enschede Netherlands

ISBN: (纸本)9789887581543

This paper aims to achieve scalable exact output synchronization for discrete-time homogeneous multi-agent systems in the presence of disturbances and measurement noise with known frequencies. The key contribution of this paper is on the distributed protocol that only uses the information of agent models, rather than the communication network information and the agent number, so as to achieve the scalable exact synchronization under disturbances and measurement noise. The validity of the protocol is verified by numerical simulations with arbitrarily chosen number of agents. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

Developing Efficient Game Theory Approaches for Spectrum Sharing in 6G Networks 5th

Developing Efficient Game Theory Approaches for Spectrum Sha...

引用

5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Ramola, Abhishek C. Francis, Jerrin Joe Savita Murugan, R. Department of Electrical Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India

ISBN: (纸本)9789819780426

This paper provides the development of green game idea procedures for spectrum sharing in upcoming 6G cellular networks. As dynamic spectrum get entry to keeps to advantage commercial interest, the want to broaden a sustainable framework to make sure powerful and relaxed spectrum sharing arises. To this stop, sport principle methods are seen as a legitimate candidate to facilitate robust spectrum sharing in 6G networks. This paper offers unique attention to the area of spectrum sharing and how the underlying game theory procedures may be leveraged to percentage spectrum efficiently. After an intensive review of existing methods and strategies, an overall performance evaluation of the numerous strategies is provided. Subsequently, the paper gives insights at the potential of game concept strategies in future 6G networks. Moreover, much game theoretic equipment are used for analytical as well as simulation experiments if you want to higher apprehend the dynamics of the spectrum sharing. Basic, this paper examines the effectiveness of each analytical and simulation-based totally game theoretic fashions for spectrum sharing in 6G networks, and gives a new version which may be used to improve the spectrum sharing dynamics in such networks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Spread spectrum communication

来源：评论

学校读者我要写书评

暂无评论

Robust Deep Learning Empowered Real Time Object Detection for Unmanned Aerial Vehicles based Surveillance Applications

引用

Journal of Mobile Multimedia 2023年第2期19卷 451-476页

作者： Ranjith, C. Prasanna Hardas, Bhalchandra M. Khaja Mohideen, M. Syed Nijil Raj, N. Robert, Nismon Rio Mohan, Prakash Faculty in Information Technology Department University of Technology and Applied Sciences Shinas Oman Electronics Engineirng Dept Shri Ramdeobaba College of Enginering and Management Nagpur India Department of Information Technology University of Technology and Applied Science Salalah Oman Department of Computer Science and Engineering Younus College of Engineering and Technology Kollam India Department of Computer Science Christ University Bangalore India School of Computer Science and Engineering Vellore Institute of Technology Vellore India

Surveillance is a major stream of research in the field of Unmanned Aerial Vehicles (UAV), which focuses on the observation of a person, group of people, buildings, infrastructure, etc. With the integration of real time images and video processing approaches such as machine learning, deep learning, and computer vision, the UAV possesses several advantages such as enhanced safety, cheap, rapid response, and effective coverage facility. In this aspect, this study designs robust deep learning based real time object detection (RDL-RTOD) technique for UAV surveillance applications. The proposed RDL-RTOD technique encompasses a two-stage process namely object detection and objects classification. For detecting objects, YOLO-v2 with ResNet-152 technique is used and generates a bounding box for every object. In addition, the classification of detected objects takes place using optimal kernel extreme learning machine (OKELM). In addition, fruit fly optimization (FFO) algorithm is applied for tuning the weight parameter of the KELM model and thereby boosts the classification performance. A series of simulations were carried out on the benchmark dataset and the results are examined under various aspects. The experimental results highlighted the supremacy of the RDL-RTOD technique over the recent approaches in terms of several performance measures. © 2022 River Publishers.

关键词： computer vision deep learning image processing object detection Surveillance unmanned aerial vehicles

来源：评论

学校读者我要写书评

暂无评论

Evolving ATM Networks for High Volume Transactions 5th

Evolving ATM Networks for High Volume Transactions

引用

5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Impa, B.H. Alam, Intekhab Kavitha, R. Prajapati, Sandhya School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Civil Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Manduwala Dehradun Navgaon India

ISBN: (纸本)9789819780426

ATM networks are evolving to guide excessive extent transactions and offer new features which includes increased safety, scalability, and cost performance. To lessen value, Banks are utilizing personal cloud environments to host their ATMs, whilst banks are looking for to deploy new offerings that assist their customers provide a higher enjoy. To enhance protection, banks are searching at encrypting data, and leveraging biometric authentication methods. Banks also are seeking to extend their offerings utilization of analytics to better goal purchaser advertising campaigns. Sooner or later, banks are adopting the use of micro services and disbursed architectures to enable building an extra scalable infrastructure that can scale horizontally with minimal effort. A majority of these advances are main to ATM networks which are efficient, comfy and dependable. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Sales

来源：评论

学校读者我要写书评

暂无评论

Machine Vision for Measurement Accuracy in Industrial Automation 15

Machine Vision for Measurement Accuracy in Industrial Automa...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Ezhilarasan, G. Singh, Vaishali Upadhyay, Ramakant Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Himachal Pradesh India Department of Computer Science Engineering Sanskriti University Uttar Pradesh Mathura India

ISBN: (纸本)9798350370249

Commercial automation has been a powerful device for enhancing productivity, decreasing charges, and increasing performance. In particular, system vision systems have enabled the implementation of advanced automation answers, allowing accurate and rapid quality measurements and inspections. This paper examines the cutting-edge nation of the use of machine imaginative and prescient systems in industrial automation, highlighting the opportunities they provide in phrases of increasing dimension accuracy. It examines the specific sorts of device vision structures to be had, their advantages and boundaries, as well as their ability for improving the exceptional of business automation structures. It also addresses the challenges that ought to be overcome to make certain full adoption of such structures, as well as the strategies for fixing these challenges, inclusive of the improvement of progressed algorithms and laptop imaginative and prescient additives, and training applications for industrial engineers. This paper affords a comprehensive evaluation of associated studies and enterprise standards, permitting readers to gain a better expertise of the development of machine vision systems in industrial automation and to become aware of possibilities to improve business dimension accuracy. © 2024 IEEE.

关键词： Office automation

来源：评论

学校读者我要写书评

暂无评论

Unraveling Disease-Specific Diffusion Patterns in Human Brain Using Diffusion Tensor Image Analysis 5th

Unraveling Disease-Specific Diffusion Patterns in Human Brai...

引用

5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Prajapati, Sandhya Bhagawati, Rupam Alam, Intekhab Jebakumari, S. Adlin Department of Electrical Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India

ISBN: (纸本)9789819780426

Diffusion tensor imaging (DTI) is a feasible approach to have a look at the structural connectivity of neuronal networks in vivo, as it presents insights into the microstructural and molecular properties of white depend fiber bundles. On this study, we used superior DTI and diffusion tensor image evaluation to analyze the unique diffusion patterns of several distinct diseases in human mind. We obtained statistics from healthful controls and cohorts of sufferers with a range of sicknesses, along with stroke, annoying mind injury, Alzheimer’s ailment, and Parkinson’s ailment, in addition to from postmortem brains of each wholesome and diseased people. Our findings emphasize the capability of the use of this technique to increase ailment-precise structural networks biomarkers for diagnosis and control of neurological illnesses. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Diffusion tensor imaging

来源：评论

学校读者我要写书评

暂无评论

Identifying Acute Disseminated Encephalomyelitis with Time Series Analysis 5th

Identifying Acute Disseminated Encephalomyelitis with Time S...

引用

5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Pallavi, M. Mishra, Awakash Kudari, Jayashree M. Belwal, Ankit School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Civil Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India

ISBN: (纸本)9789819780426

Acute disseminated encephalomyelitis (ADEM) is an extraordinary immune-mediated disease that influences the mind and spinal cord, central to the unexpected onset of neurologic symptoms. Time series evaluation can be used to become aware of ADEM in patients. Mainly, statistical analysis of the temporal styles of mind imaging and immunological parameters has proven effective for diagnosing ADEM in medical settings. Such material styles offer essential clues about disease development, which can be leveraged to diagnose ADEM patients appropriately. Acute disseminated encephalomyelitis (ADEM) is a critical degenerative sickness of the imperative nervous device, characterized by a rapid onset of neurologic signs and significant infection of the mind and spinal twine. Early analysis of ADEM is critical to initiate appropriate remedies and reduce long-term incapacity. In this look, we advocate the usage of time collection analysis to discover neurological patterns related to ADEM from the brain indicators of sufferers. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Time series

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence Based Sentence Level Sentiment Analysis of COVID-19

引用

computer systems science & engineering 2023年第10期47卷 791-807页

作者： Sundas Rukhsar Mazhar Javed Awan Usman Naseem Dilovan Asaad Zebari Mazin Abed Mohammed Marwan Ali Albahar Mohammed Thanoon Amena Mahmoud Department of Software Engineering University of Management and TechnologyLahore54770Pakistan School of Computer Science The University of SydneySydneyAustralia Department of Computer Science College of ScienceNawroz UniversityDuhok42001Kurdistan RegionIraq College of Computer Science and Information Technology University of AnbarAnbar31001Iraq Department of Computer Science Umm Al Qura UniversityMecca24211Saudi Arabia Computer Science Department Faculty of Computers and InformationKafrelsheikh UniversityKafrelsheikhEgypt

Web-blogging sites such as Twitter and Facebook are heavily influenced by emotions,sentiments,and data in the modern ***,a widely used microblogging site where individuals share their thoughts in the form of tweets,has become a major source for sentiment *** recent years,there has been a significant increase in demand for sentiment analysis to identify and classify opinions or expressions in text or *** or expressions of people about a particular topic,situation,person,or product can be identified from sentences and divided into three categories:positive for good,negative for bad,and neutral for mixed or confusing *** process of analyzing changes in sentiment and the combination of these categories is known as“sentiment analysis.”In this study,sentiment analysis was performed on a dataset of 90,000 tweets using both deep learning and machine learning *** deep learning-based model long-short-term memory(LSTM)performed better than machine learning *** short-term memory achieved 87%accuracy,and the support vector machine(SVM)classifier achieved slightly worse results than LSTM at 86%.The study also tested binary classes of positive and negative,where LSTM and SVM both achieved 90%accuracy.

关键词： COVID-19 artificial intelligence machine learning deep learning sentimental analysis support vector classifier

来源：评论

学校读者我要写书评

暂无评论

Deep learning-based cognitive digital twin system for wrist pulse diagnostic and classification 2nd

Deep learning-based cognitive digital twin system for wrist ...

引用

2nd International Conference on Next-Generation Computing and information systems, ICNGCIS 2023

作者： Chaudhary, Jitendra Kumar Parimalam, T. Alghayadh, Faisal Yousef Keshta, Ismail Soni, Mukesh Degadwala, Sheshang School of Computing Graphic Era Hill University Bhimtal Campus Uttrakhand India Department of Computer Science Nandha Arts and Science College Tamilnadu Erode India Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Dr. D. Y. Patil Vidyapeeth Pune Dr. D. Y. Patil School of Science & Technology Tathawade Pune India Department of Computer Engineering Sigma University Gujarat Vadodara India

ISBN: (纸本)9781032738659

In analyzing and recognizing wrist pulse signals, it isn’t easy to mine the nonlinear information of wrist pulse signals using analysis methods such as time and frequency. Traditional machine learning methods require the manual definition of features and cannot perform self-learning of features. A cognitive digital twin technique for pulse analysis and recognition based on threshold-less recursive graph and CNN is proposed. The wrist pulse signal is converted into a threshold-free recursive graph based on the nonlinear dynamics’ theory. The VGG-16 CNN automatically extracts the nonlinear features of the recursive graph, and a pulse condition classification model is established. Experimental finding several that the classification of the proposed method accuracy can reach 98.14%, as compared with the existing pulse classification methods. This study offers a novel concept and strategy for classifying pulse signals, and it has application to the objectification of pulse diagnosis. © 2025 The Author(s).

关键词： Graphic methods

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：