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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68642 条记录，以下是4731-4740 订阅

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Adversarial Patch Attacks Against Aerial Imagery Object Detectors Based on Interpretable Guidance

Adversarial Patch Attacks Against Aerial Imagery Object Dete...

引用

2023 IEEE international conference on Dependable, Autonomic and Secure Computing, 2023 international conference on Pervasive Intelligence and Computing, 2023 international conference on Cloud and Big Data Computing, 2023 international conference on Cyber science and technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Liu, Fengyi Lian, Zhichao School of Cyberspace Security Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9798350304602

Although image recognition and classification methods based on deep neural networks (DNNs) have accomplished remarkable achievements in the domain of computer vision, more and more research in recent years has shown that these models may have vulnerabilities that can be easily exploited by attackers, leading to incorrect output results. Especially in the realm of object detection, the incorporation of meticulously crafted patches onto images can potentially deceive DNN-based detectors, resulting in erroneous output outcomes. These patches can be carefully designed to greatly interfere with and mislead the output results of deep neural networks. These misleading output results may lead to serious security issues and losses, so it is becoming increasingly important to study and strengthen the robustness and security of DNNs based target detectors. However, previous methods did not consider the interpretability of the model, and this paper proposes a new mothed to adversarial patch attacks. First, we employ the model interpretable algorithm Grad-CAM to obtain the patch's location within the model's region of interest for the target. Subsequently, we calculate the precise patch placement and apply it accordingly. Following that, we utilize a loss function to optimize patch, ensuring its effectiveness. The experimental results obtained from the DOTA dataset indicate that our proposed method effectively degrades the performance of the target detection model. Secondly, we conducted experiments to improve the transferability of adversarial patches across different models, and verified that using patches to cover the regions of interest in the model improves the transferability of patches. © 2023 IEEE.

关键词： Deep neural networks

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An Adaptive Dynamic Service Flow Control Strategy Based on trTCM Algorithm

An Adaptive Dynamic Service Flow Control Strategy Based on t...

引用

2023 international conference on Intelligent Systems, Communications, and computer Networks, ISCCN 2023

作者： Yongge, Shi Yangming Yongchong, Wu GongQing Institute of Science and Technology Gongqingcheng Jiangxi332020 China Jiujiang Vocational and Technical College Jiujiang Jiangxi332007 China

ISBN: (纸本)9781510666238

When the network has burst high concurrent access traffic, the traffic allocated to each node in the cluster will exceed the maximum processing capacity of the machine, which needs to be solved by applying flow control technology. For this reason, this paper studies the flow control technology under the microservice architecture, and proposes an adaptive dynamic service flow control strategy based on the srTCM algorithm, which can dynamically regulate and differentiate the tasks entering the service node according to the request type and the running state of the machine. Experiments show that the research results of this paper are better than the common current limiting schemes. © 2023 SPIE. All rights reserved.

关键词： Concurrency control

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Flink Stream Big Data Parallel Operator Design and Topsis Performance Evaluation 4

Flink Stream Big Data Parallel Operator Design and Topsis Pe...

引用

4th international conference on computer, Big Data and Artificial Intelligence, ICCBD+AI 2023

作者： Zhang, Hang Changchun University of Science and Technology School of Computer Science and Technology China

ISBN: (纸本)9798350373233

The process of streamlining big data processing encounters several challenges, including managing extensive data volumes and ensuring high real-time performance. Flink has emerged as the favored technical solution in the realm of big data streaming processing due to its provision of numerous parallel operators. However, the effective design of these parallel operators and the performance evaluation process are pivotal for achieving efficient streaming data processing. Consequently, this study has formulated a series of parallel operators and assessed their performance using the Technique for Order of Preference by Similarity to Ideal Solution (Topsis) algorithm. The findings of this investigation emphasize the significance of operator design in streamlining big data processing. This research offers substantial support and serves as a valuable reference for resource optimization and performance evaluation. These outcomes have profound implications, not only in managing vast real-time data streams but also in the development of applications and systems aimed at addressing the challenges posed by large-scale data © 2023 IEEE.

关键词： Big data

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Adult Income Classification using Machine Learning Techniques

Adult Income Classification using Machine Learning Technique...

引用

2023 IEEE conference on computer Applications, ICCA 2023

作者： Moe, Ei Ei Win, Si Si Mar Lai Khine, Kyi Lai University of Comuter Studies Faculty of Computer Science Taungoo Myanmar University of Comuter Studies Faculty of Computer Science Yangon Myanmar

ISBN: (纸本)9781665435994

Nowadays, the economic growth of country is often measured by the increasing gross domestic product (GDP). GDP is an effective indicator in the national economic accounting system and has a significant reference function for political decision and regional development. GDP improvement shows economic development level, national income and spending power of a country or region. In actual accounting, three methods can be used to compute GDP namely production, expenditure, or income approach which respectively reflect gross domestic product and its composition from different aspects. This paper is presented to predict the GDP of person based on adult income data with the age from 17 to 90 using popular supervised learning techniques. The models are tested on more than 30000 data records of over forty countries especially United States. The experiments show that the different results between Naïve Bayes, J48 and Random Forest classifiers. © 2023 IEEE.

关键词： Decision trees

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SysML modeling tools for improved storage efficiency 4

SysML modeling tools for improved storage efficiency

引用

4th international conference on Signal Processing and computer science, SPCS 2023

作者： Jin, Qinchao Yang, Peihao Wang, Tiantian Wu, Xianghu Wang, Kechao School of Computer Science and Technology Harbin Institute of Technology Harbin China School of Information Engineering Harbin University Harbin China

ISBN: (纸本)9781510672505

With the development and widespread application of Model-Based Systems Engineering (MBSE) in the aerospace domain continue to grow, System Modeling Language (SysML) has become increasingly important as the most popular modeling language in MBSE. It is crucial to provide developers with an efficient and secure SysML editing tool to enhance their productivity. However, our research has revealed issues with the existing SysML editing tools, particularly in terms of data storage, resulting in a decline in efficiency as project data grows. Therefore, this paper proposes a GEF-based SysML development tool that supports developers in creating, editing, and exporting graphics. This tool addresses the data storage issues, improving development efficiency. Additionally, we present a model validation approach and extend the existing validation rules to ensure the correctness, reliability, and security of graphical elements and diagrams. © 2023 SPIE.

关键词： Modeling languages

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Research on Knowledge Fusion Optimization System Based on computer Large-Scale Heterogeneous Network Big Data

Research on Knowledge Fusion Optimization System Based on Co...

引用

2023 IEEE international conference on Sensors, Electronics and computer Engineering, ICSECE 2023

作者： Xiaogan, Chen Peng, Shu Xiaohan, Lai Jiabin, Huang Qing, Nie State Grid Zhejiang Electric Power Co. Ltd. Hangzhou China Yingda Media & Investment Group Co. Ltd. Beijing China

ISBN: (纸本)9798350313734

Network big data refers to the big data generated by the interaction and fusion of "people, machines and things"in the network space and available on the Internet. In this paper, from the perspective of ontology-based knowledge representation, network knowledge is represented in the form of five-tuples such as instance, attribute, domain set, relation and concept. Then, from the perspective of complex system, the new research perspective of deep learning technology and the new technology trends of grain computing in information fusion are analyzed, and the feasibility of the integration and expansion of grain computing and deep learning is speculated. A new overlapping community detection algorithm based on modularity optimization is designed. It is found that the framework can solve the dynamic update of network big data and the integration and reorganization of existing professional knowledge base to a certain extent. It can effectively guarantee the construction of domain knowledge base and improve its coverage and timeliness. © 2023 IEEE.

关键词： Heterogeneous networks

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Research on improved algorithm of logistics optimization based on big data 2

Research on improved algorithm of logistics optimization bas...

引用

2nd international conference on Big Data, Information and computer Network, BDICN 2023

作者： Xin, Ming Zhu, Haipeng Guangdong Polytechnic of Science and Technology School of Business Zhuhai China

ISBN: (纸本)9798350321364

As an important part of the modern service industry, the healthy development of the logistics industry has a very positive impact on improving the quality of the national economy and promoting the supply reform. With the arrival of the new economic era, the impact of the development of science and technology on logistics is deepening, the penetration speed is accelerating, and the competition between logistics industries is becoming increasingly fierce. For the logistics industry, in the face of endless new technologies, if you want to gain competitive advantage, you must improve the management level, especially the cost management level. In the information age, the goal of enterprise cost management should not be limited to the enterprise itself, but should be the cost management of the entire value chain. Therefore, it is of great significance to study the value chain management of logistics enterprises in the context of big data. © 2023 IEEE.

关键词： Big data

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Research on Filter Testing Based on Microwave Power Devices 5

Research on Filter Testing Based on Microwave Power Devices

引用

5th IEEE international conference on Power, Intelligent Computing and Systems, ICPICS 2023

作者： Wu, Han Yao, Ding Zeng, Ziyue Jiang, Yong Yuan, Yuan Test Center Jiangsu Automation Research Institute Lianyungang China

ISBN: (纸本)9798350333442

With the advancement of science and technology and the arrival of the information age, microwave technology has made rapid progress. As an important branch of radio electronics, microwave technology has been widely applied in the fields of communication, navigation, radar, and electronic warfare. Based on this background, this article conducted research on filter testing based on microwave power devices. Firstly, the relevant theories and techniques of microwave power measurement were studied, and the framework model and constituent modules of commonly used measurement systems were elaborated. Then, based on the module of the switch filter array, the design and implementation were carried out. Finally, the testing methods and results of the switch filter array were analyzed. The results show that the performance of the frequency-selective components is generally similar to that of individual tests, and it basically meets the performance requirements of the system for the switch filter array. © 2023 IEEE.

关键词： Electronic warfare

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Research on Multi-Scale Line Feature Extraction Algorithm Based on LSD 3

Research on Multi-Scale Line Feature Extraction Algorithm Ba...

引用

3rd international conference on Electronic Information Engineering and computer science, EIECS 2023

作者： Zhu, Yalan Bai, Keqiang Zuo, Lu Jiang, Hesong Southwest University of Science and Technology School of Information Engineering Sichuan Mianyang China

ISBN: (纸本)9798350316674

Line segment detector (LSD) algorithm is widely used in many systems that rely on image processing, and plays a decisive role in the stable operation of the system. To solve the problem that the line segment features extracted by traditional LSD algorithm are many short lines, and the line features cannot be extracted in some environments. In this paper, a multi-scale line feature extraction algorithm based on LSD is proposed. Firstly, a multi-scale space is added to the line segment extraction to reduce the missed detection of the line segment and combine the line segment with similar spatial position. Then input the image of the line segment extractor to sample and generate scale space to extract the preselected line segment set. Finally, the preselected line segment set is optimized by merging and fusion. Through experiment, this method is compared with the original method to extract the characters of more, at the same time to ensure the accuracy of the extracted features. © 2023 IEEE.

关键词： Feature extraction LSD Multi-scale space

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ARTIFICIAL INTELLIGENCE ASSISTED SERVICE MARKETING USING DEEP ASSISTED NEURAL NETWORK

ARTIFICIAL INTELLIGENCE ASSISTED SERVICE MARKETING USING DEE...

引用

2023 IEEE international conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering, RMKMATE 2023

作者： Shanthana, S. Gopal, Vidhya Navulla, Durgaprasad Seal, Sudeshna Sohail, Mohammed Ali Paul, Gunti Anil Rajalakshmi Institute of Technology Tamilnadu Chennai India Department of Computer Science and Engineering Sona College of Technology Tamilnadu Salem India Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Guntur India OmDayal Group of Institutions West Bengal Uluberia India Department of Computer and Network Engineering College of Computer Science and Information Technology Jazan University Jazan Saudi Arabia Department of Mechanical Engineering Karunya Institute of Technology and Sciences Tamilnadu Coimbatore India

ISBN: (纸本)9798350305708

Improving marketing abilities, the quality of one product, and one connections with one target audience are at the service marketing approach. The marketing of goods and services can both be considered to come within the scope of this category. This data is stored in a centralized location in these databases for ease of access and analysis. Based on the findings of this study, AI has played a crucial role in big data analytics, making it possible to foresee and provide guided experiences that are individualized based on the needs of customers. In this paper, we develop a AI assisted customer support system to deliver experiences that result in advocates and consumers that remain loyal over time, the usage of AI and predictive analytics is crucial. © 2023 IEEE.

关键词： artificial intelligence neural network Service marketing validation

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