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检索条件"任意字段=International Conference on Big Data Intelligence and Computing, DataCom 2022"

共 1358 条记录，以下是211-220 订阅

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SRCPT: Spatial Reconstruction Contrastive Pretext Task for Improving Few-Shot Image Classification 24

SRCPT: Spatial Reconstruction Contrastive Pretext Task for I...

引用

16th international conference on Machine Learning and computing (ICMLC)

作者： Wang, ZhenBang Duan, PengFei Rong, Yi Wuhan Univ Technol Sch Comp Sci & Artificial Intelligence Wuhan Hubei Peoples R China Wuhan Univ Technol Sanya Sci & Educ Innovat Pk Sanya Hainan Peoples R China

ISBN: (纸本)9798400709234

Self-supervised learning (SSL) has been widely applied in the pretraining phase of models. Among these SSL methods, the various data augmentation used in contrastive learning for constructing positive and negative sample pairs conveniently contribute to alleviating the issue of data scarcity in few-shot learning (FSL) tasks. Therefore, many approaches have introduced contrastive learning into FSL tasks. However, most of these methods only utilize the global embedding information of the entire image, making it challenging to capture and fully leverage the local visual information and structural details of image samples. To address this, we proposes a novel Spatial Reconstruction Contrastive Pretext Task (SRCPT) to enhance the FSL training objective. By constructing a two-branch network, the model can use local patches of the image for feature map reconstruction and employ spatial reconstruction weights to create a contrastive learning objective. The enhanced FSL objective of SRCPT encourages the model to capture more transferable spatial structures and local feature information, enabling the model to adapt well to new categories even with a few samples. Extensive experiments demonstrate that our proposed SRCPT method achieves state-of-the-art performance in three popular benchmark datasets across three types of few-shot image classification tasks.

关键词： few-shot learning local spatial feature reconstruction contrastive learning

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Transwarp data Cloud: A Stable, Efficient, and Intelligent data Application Cloud Platform 7

Transwarp Data Cloud: A Stable, Efficient, and Intelligent D...

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7th IEEE international conference on Smart Cloud, SmartCloud 2022

作者： Yang, Hongshan Liu, Wanggen Liu, Chenyun Wang, Tianqing Peng, Lei Transwarp Technology Co. Ltd Shanghai China Shanghai Big Data Center Shanghai China

ISBN: (数字)9781665451796

ISBN: (纸本)9781665451796

Large value hidden in big data has motivated enterprises to transform from information technology magnates to data technology magnates. Cloud computing and artificial intelligence offer eligible solutions for extracting information in big data, and integration of the above three renders the data cloud platform. In this paper, we specify Transwarp data Cloud (TDC), a stable, efficient, and intelligent data application cloud platform, which fuses data cloud, analytics cloud, and application cloud to manage all types of applications and services while sharing a well-maintained underlying infrastructure layer. In addition, we identify a general application framework based on TDC, by which various data-driven applications can be supported, and then we discuss some popular applied domains including big data, Application Development and Management, and artificial intelligence. With powerful tools and flexible application support, TDC can help enterprises with the innovation and revolution of business in the era of big data. © 2022 IEEE.

关键词： big data

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Synergizing Four Different computing Paradigms for Machine Learning and big data Analytics 1

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1st Serbian international conference on Applied Artificial intelligence, SICAAI 2022

作者： Milutinović, Veljko Salom, Jakob IPSI Ltd Belgrade Serbia

ISBN: (数字)9783031297175

ISBN: (纸本)9783031297168

This article presents and analyses four computing paradigms that are present in today’s IT programming world - Control Flow, data Flow, Diffusion Flow, and Energy Flow. It compares their main properties, points out what purposes each has, and describes what are their advantages and disadvantages. In the third part of this article, the Authors speculate on the possible architecture of a supercomputer on a chip and in the fourth part, they suggest the optimal distribution of resources for a specified set of Civil engineering applications. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： data Analytics

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Artificial intelligence and Law: A Bibliometric Insight into Academic Publications and Research Trends 12

Artificial Intelligence and Law: A Bibliometric Insight into...

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12th IEEE international conference on Intelligent data Acquisition and Advanced computing Systems: Technology and Applications, IDAACS 2023

作者： Aydemir, Emrah Cebeci, Halil Ibrahim Sakarya University Sakarya Business School Division of Management Information Systems Esentepe Campus Sakarya54187 Turkey

ISBN: (纸本)9798350358056

In this study, the analysis of artificial intelligence, machine learning, and deep learning studies in the field of law over the past 20 years was conducted. A total of 2161 data were obtained from the Scopus database, with Social Sciences selected as the subject area. The data consisted of various types such as articles, conference papers, book chapters, and books from the years 2003 to 2022. Several analyses were employed in the data analysis, including the number of studies per year, distribution of studies by subject areas, distribution of studies by country, distribution of studies by number of authors, and distribution of trend topics. The research findings revealed a significant increase in the number of studies after 2017, with a focus on topics such as big data, robots, ethics, rights, data protection, autonomous weapons, and natural language processing. In terms of the number of publications, Italy, Australia and Brazil draw attention after the USA, China and England. While the focus of the relations between the authors was the EU countries, there was an intense cooperation between China-USA and Australia-EU countries. The growing number of studies in this area suggests that artificial intelligence will make further progress and become more prominent within the legal field in the near future. © 2023 IEEE.

关键词： artificial intelligence Bibliometric Analysis law

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The Study of Multi-type computing Power Trading Mechanism in computing Power Network Based on Blockchain and Combinatorial Double Auction 24

The Study of Multi-type Computing Power Trading Mechanism in...

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4th international conference on Artificial intelligence, big data and Algorithms, CAIBDA 2024

作者： Zhao, Yue Wang, Jizhi Kong, Lingrui Sui, Tongtong Shandong Computer Science Center National Supercomputer Center in Jinan Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Provincial Key Laboratory of Industrial Network and Information System Security Qilu University of Technology Shandong Academy of Sciences Jinan Shandong China Quancheng Laboratory Jinan Key Laboratory of Digital Security Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Qilu University of Technology Shandong Academy of Sciences Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan Shandong China

ISBN: (纸本)9798400710247

The advancement of 5G and mobile internet technologies has propelled the development of emerging businesses and applications, demanding higher requirements for network bandwidth and computational resources. To address this challenge, the computing power network (CPN) has emerged. The CPN integrates computing and networking in depth, achieving collaborative allocation of distributed computing resources, enhancing the efficient utilization of computing resources, and improving user experiences in network services. However, in the development of fields such as Extended Reality (XR), Smart Healthcare, Connected Vehicles, and Artificial intelligence (AI), there is a multidimensional, complex, and rapidly growing demand for computing resources. Therefore, it is crucial to establish a trading mechanism that integrates multiple computing resources in CPN. In this paper, a computing power trading scheme based on blockchain and combinatorial double auction is proposed. Firstly, a computing power trading system based on blockchain was designed, leveraging the decentralized and highly secure characteristics of blockchain technology to enhance the security of computing power transactions. Furthermore, a multi-type computing power trading mechanism (MCPT) based on blockchain and combinatorial double auction was introduced. The use of combinatorial double auctions as an incentive mechanism enables the trading of multiple computing power resources and results in high social welfare. Moreover, a discrete rime optimization algorithm (DRIME) is designed in the proposed mechanism (MCPT) to better solve the computing trading problem. Through simulation experiments, the effectiveness of the approach is validated. © 2024 Copyright held by the owner/author(s).

关键词： computing power

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Risk and Return of Securities Investment in the Context of big data and Artificial intelligence 12th

Risk and Return of Securities Investment in the Context of B...

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12th international conference on Frontier computing, FC 2022

作者： Chen, Xuanyou Deng, Yanyi School of Business Nanning College of Technology Guangxi Guilin China

ISBN: (纸本)9789819914272

The advent of the era of big data has had a huge impact on all sectors of society. In recent years, my country's Internet technology has developed rapidly and its penetration rate has become higher and higher. In economic life, securities investment is an important and common financial behavior. The analysis of its risks and returns is a behavior that investors are more concerned about. To this end, this article proposes investment analysis and income analysis under artificial intelligence, with the purpose of improving the accuracy of the analysis. This article mainly uses experimental method, case analysis and comparative method to explain the risks and returns of securities investment. The experimental results show that when the risk value is 0, people tend to invest conservatively. Portfolio theory shows that choosing multiple securities for portfolio investment can effectively reduce risks. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： big data

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KSTA: a strategy for scheduling data-intensive workflows onto cloud computing resources 9

KSTA: a strategy for scheduling data-intensive workflows ont...

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9th international conference on Advanced Cloud and big data, CBD 2021

作者： Zheng, Wei Lin, Peixuan Yang, Tongzhou Xiamen University Department of Computer Science Xiamen China Tianjin University College of Intelligence and Computing Tianjin China

ISBN: (纸本)9781665407458

The problem of scheduling data-intensive workflows in cloud environment has not been fully studied. There is a large amount of communication between data-intensive workflow tasks, and the communication time is often not considered. This paper focuses on the problem of scheduling data-intensive workflows with time constraints on cloud computing. The scheduling goal is to maximize resource utilization rate and job success rate, which are closely related to the interests of service providers and users. In this paper, a scheduling strategy based on key subtasks has been proposed and evaluated along with four other strategies that can be used to schedule data-intensive workflows. It can effectively improve the resource utilization rate and the job success rate. © 2022 IEEE.

关键词： Scheduling

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Visualization Research of big data in Higher Education Based on the Web of Science 3

Visualization Research of Big Data in Higher Education Based...

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3rd international conference on Electronics, Communications and Information Technology, CECIT 2022

作者： She, Linwei Lai, Liqi Jinan University International Business School Zhuhai519070 China Jinan University GBA and B&R International Joint Research Center for Smart Logistics Zhuhai519070 China Modern Education Technology Center Jinan University Zhuhai519070 China

ISBN: (纸本)9798350331974

With the rapid development of information technology such as artificial intelligence and cloud computing, big data of higher education has received a lot of attention. This article uses the visual software Citespace from 2013 to 2022 to research higher education in big data in the Web of Science database. Through visual analysis, and uses of the keyword co-occurrence function and cluster analysis function, this article clarifies the main research directions, key documents, hotspots, and limitations in the field of big data in higher education, education big data technology, learning behavior analysis, learning style exploration, education resource management, and personalized teaching reform are the development direction and research hotspots. This article can provide readers and other researchers with some references and help. © 2022 IEEE.

关键词： big data

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Construction of an Artificial intelligence Evaluation System for the Effect of Modern Informatization Ability and English Practice Under the Background of New Liberal Arts 1

Construction of an Artificial Intelligence Evaluation System...

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1st international conference on Applied Artificial intelligence and computing, ICAAIC 2022

作者： Yu, Ruihua School of Foreign Languages Bohai University Liaoning Jinzhou121000 China

ISBN: (纸本)9781665497107

This paper studies the artificial intelligence evaluation system of modern informatization capabilities and the effectiveness of English practice under the background of the new liberal arts. The construction of 'new liberal arts' needs to be guided by social needs, fully integrate internal and external resources, and multi-party collaboratively cultivate interdisciplinary applied talents. Practical teaching is an important link in cultivating students' practical and innovative abilities, and the discipline of investment involves multiple disciplines, and it is necessary to closely integrate modern information technologies such as artificial intelligence and big data to build a practical teaching system. Build an editorial power evaluation system under the artificial intelligence perspective, systematically evaluate micro-editing power, meso-editing power, and macro-editing power from the external, internal and external dimensions, and causal dimensions, respectively. © 2022 IEEE.

关键词： Informatization

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Research on energy consumption prediction model based on big data platform and random forest algorithm

Research on energy consumption prediction model based on big...

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2022 international conference on data Analytics, computing and Artificial intelligence, ICDACAI 2022

作者： Cai, Wenjia He, Xing Wu, You Zhang, Jiawen Ran, Yanchun Li, Linghua Metering Center of State Grid Hubei Electric Power Co. Ltd. Wuhan430000 China

ISBN: (数字)9781665454704

ISBN: (纸本)9781665454704

The distributed big data analysis platform is built by using Hadoop, Spark, Hbase, etc. Based on this platform, a healthy data set is obtained through data collection and pre-processing, and an energy consumption regression prediction model based on parallel random forest algorithm is established, and the relationship between the input, model parameters and output of the random forest prediction model is comprehensively analyzed and compared. The parameters such as the number of decision trees, the depth of decision trees and the maximum number of splits are compared and analyzed on the accuracy, operation time and complexity of the training model, and the optimal parameters of the prediction model are obtained to realize the accurate prediction and soft measurement calculation of power supply coal consumption. © 2022 IEEE.

关键词： Forecasting

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