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

共 68880 条记录，以下是1281-1290 订阅

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Ground Plane Segmentation and Outliers Removal in Point Clouds of Electrical Substations 3

Ground Plane Segmentation and Outliers Removal in Point Clou...

引用

3rd IEEE international conference on Information technology, Big Data and Artificial Intelligence, ICIBA 2023

作者： Wang, Fei Fan, Zikai Li, Yan Xu, Lai Shi, Liang Qian, Kun Economic Research Institute State Grid Jiangsu Electric Power Co. Ltd. Nanjing China Southeast University School of Automation Nanjing China

ISBN: (纸本)9781665490788

With the increasing popularity of 3D laser scanning technology, automatic modeling of 3D point clouds of substation scenes is crucial for applications such like the digitalization of electrical substations. However, the point clouds obtained by the 3D laser scanner is noisy. In addition to the equipment that needs to be extracted, it also contains ground plane data, vegetation data, power lines, and others. In this paper, we propose a ground plane segmentation and outliers removal method as a fundamental step toward substation entity modeling. In particular, we have developed an automatic ground plane removal method and an interactive method for removing outliers. Finally, the effectiveness of the model proposed in this paper is validated through a case study in a substation point cloud. © 2023 IEEE.

关键词： Three dimensional computer graphics

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An IoT Solutions for Ungulates Attacks in Farmland 2

An IoT Solutions for Ungulates Attacks in Farmland

引用

2nd international conference for Innovation in technology, INOCON 2023

作者： Raju, Ratheesh Thasleema, T.M. Central University of Kerala Department of Computer Science Kasaragod Periye India

ISBN: (纸本)9798350320923

Agriculture is considered to be a significant contributor to the global financial system and human diets. It has been recognized as the country's primary source of income and employment. So, it's really important to protect crops from various dangerous hazards, such as diseases, insects, bird and animal attacks, high atmospheric temperature, etc., and also from weak irrigation systems, poor soil quality, weeds management, etc. Specific insect attacks and diseases have long been a primary crop sector concern. computer vision (CV)-based automatic insect and disease detection methods are used in smart farming systems because of their high cost-effectiveness and efficient automation. This paper gives an overview of the use of Machine Learning (ML), Deep Learning (DL), and the Internet of Things (IoT) in agriculture to protect crops from various dangerous hazards and proposes an automatic Animal-Repelling System (ARS). This study implements a system based on IoT to protect crops from animals. The proposed low-cost agricultural field protection system helps farmers to protect their crops and increase production yield and income. © 2023 IEEE.

关键词： Internet of things

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Discovery of Unknown Classes in Constrained Semi-Supervised Learning 2

Discovery of Unknown Classes in Constrained Semi-Supervised ...

引用

2nd international conference on Advancements in Electrical, Electronics, Communication, Computing and automation, ICAECA 2023

作者： Roopa, S. Nithya Department of Computer Science and Engineering Kumaraguru College of Technology Coimbatore India

ISBN: (纸本)9798350306811

Supervised classification models have proved their significance in research and are utilized in many key areas. However, there are some limitations for these methods. In supervised learning, adequate labelled training data are required for each class. The learned classifier can classify only the data belonging to classes for which training data is available and lacks the ability to handle the data of unseen classes. However, in real time scenarios, there may not be adequate training data for all the classes. There could also be scenarios where the classes not available in the training data appearing in the testing data. The learner is expected to have the capability to uncover the class labels for the data belonging to unseen classes. To handle this situation, methods under different learning paradigms are proposed. In this work, various semi supervised learning techniques that can handle hidden classes(clusters) are evolved. Variant of Semi Supervised EM Based-K means and Naïve Bayes are discussed. © 2023 IEEE.

关键词： Classification (of information)

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Bridging Automated Reasoning and Machine Learning for Information Analysis 2

Bridging Automated Reasoning and Machine Learning for Inform...

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2nd IEEE international conference on Futuristic Technologies, INCOFT 2023

作者： Joshi, Sarita Murugan, R. Balaji, N.V. Chandrakala, P. Deshmukh, Gopal B. Mathur, Mala Maharishi School of Business Management Maharishi University of Information Technology Uttar Pradesh India Bangalore Department of Computer Science and Information Technology Karnataka India Karpagam Academy of Higher Education Department of Computer Science Coimbatore641021 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electrical and Electronics Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Vivekananda Global University Department of Civil Engineering Jaipur India

ISBN: (纸本)9798350308846

Recent advances in automated reasoning and system studying have appreciably impacted the automation of statistics evaluation. These technologies facilitate understanding the increasingly more complicated volumes of facts in a ramification of approaches. Automatic reasoning helps decide valid solutions based on structured good judgment, while machines can pick out patterns and developments in massive datasets. Bridging those two technologies improves accuracy and efficiency in automated facts evaluation. This paper will overview present-day research on bridging automated reasoning and device-gaining knowledge for such purposes and gift novel approaches to combining the two technologies for more effective data evaluation. Discussion subjects will encompass integrating neural networks and reasoning engines, methods for addressing records incompleteness and uncertainty, and enhancement of reasoning-driven context-conscious systems. Furthermore, the paper will discover the capacity benefits that can be performed via leveraging the strengths of each automated reasoning and gadget gaining knowledge of to optimize answers for a selection of software scenarios. © 2023 IEEE.

关键词： Gaining Optimize Reasoning Selection Uncertainty

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The Application of the automation technology in the Mechanical Control System is Reflected

The Application of the Automation Technology in the Mechanic...

引用

2023 international conference on Mechatronics and Intelligent Control, ICMIC 2023

作者： Zhou, Ying Liaocheng Technician College Liaocheng Advanced Engineering Vocational School Liaocheng China

ISBN: (纸本)9781510668393

In the rapid development of social economy, the technical theory of our country has become more and more rich, and the competition between various industries will become more and more intense. In order to achieve development advantages in such a fierce competitive environment, enterprises should make innovations in production technology, form unique development advantages, and effectively improve economic benefits. On the basis of understanding the development status of enterprise machinery and mechanical automation technology, according to the structure of mechanical control system, this paper mainly analyzes the common automation technology content in the current market, and takes the automotive field as an example for empirical study. The final result shows that automation technology in mechanical control system has unique advantages. © 2023 SPIE.

关键词： Competition

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A ModelOps-Based Framework for Intelligent Medical Knowledge Extraction 1

A ModelOps-Based Framework for Intelligent Medical Knowledge...

引用

1st IEEE international conference on Medical Artificial Intelligence, MedAI 2023

作者： Ding, Hongxin Zou, Peinie Wang, Zhiyuan Zhao, Junfeng Wang, Yasha Zhou, Qiang School of Computer Science Peking University Peking China School of Software & Microelectronics Peking University Peking China School of Computer Science Peking University Research Center of Big Data Technology Nanhu Laboratory Peking China Shenzhen Emergency Medical Center Shenzhen China

ISBN: (纸本)9798350358780

Extracting medical knowledge from healthcare texts enhances downstream tasks like medical knowledge graph construction and clinical decision-making. However, the construction and application of knowledge extraction models lack automation, reusability and unified management, leading to inefficiencies for researchers and usage barriers for non-AI experts like doctors. To address these issues, we propose a ModelOps-based intelligent medical knowledge extraction framework that offers a low-code system for model construction and application. Specifically, the framework includes a dataset abstraction mechanism based on multi-layer callback functions, a reusable model training, monitoring and management mechanism, alongside a model recommendation method based on dataset similarity for quickly finding potentially suitable models for a given dataset. Our frame-work provides convenience for researchers to develop models and simplifies model access for non-AI experts like doctors. © 2023 IEEE.

关键词： Reusability

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Yolov7-ODCA: Object Detection of Pomelo Epidermis Defects Based on Improved YOLOv7 3

Yolov7-ODCA: Object Detection of Pomelo Epidermis Defects Ba...

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3rd international conference on computer science, Electronic Information Engineering and Intelligent Control technology, CEI 2023

作者： Chen, Wei Yang, Enqi Wu, Wanhan Chen, Riqing Yang, Changcai Lin, Yaohai College of Computer and Information Sciences Fujian Agriculture and Forestry University Fuzhou350002 China

ISBN: (纸本)9798350372052

The detection of pomelo epidermis defects plays an essential role in the mechanization and automation of pomelo. However, pomelo epidermis defect data possesses characteristics such as small targets and low contrasts, which brings great challenges to general object detectors. To address these issues, we propose an improved YOLOv7 network, namely YOLOv7-ODCA. The feature extraction process was improved based on the YOLOv7 network through optimization of the CBS module, and the ODCBS module was proposed by introducing the Omni-dimensional dynamic convolution (ODConv) and residual structure. This aims to enhance the feature extraction capability of CNN for low contrast images. Additionally, a Context Aggregation Block (CABlock) has been integrated in the detection head to address the issue of excessive irrelevant background information in images with small target defects. In the experiments, we compare the proposed YOLOv7-ODCA networks in the metrics of AP, AP50, precision, and recall. It achieves average accuracies exceeding all compared networks, with values of 49.8%, 92.6%, 87.6%, and 85.2%, respectively. © 2023 IEEE.

关键词： Convolution

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Research on the Application of Artificial Intelligence in computer Networks 6

Research on the Application of Artificial Intelligence in Co...

引用

6th international conference on computer Information science and Application technology, CISAT 2023

作者： Ma, Li Wuhan Donghu University China

ISBN: (纸本)9781510668546

The effective use of high technology in all sectors of society can achieve the purpose of technological empowerment and facilitate the development of education, medical, aerospace, biomedical and other fields to overcome the difficulties. The rational use of advanced technology to achieve business development goals is one of the issues that all sectors are concerned about and must study. Artificial intelligence is a technology developed based on computer technology, through which computers can imitate human consciousness and improve their "cognitive" ability, enabling them to deal with various situations in a continuous cognitive manner. The article explores the application strategies of artificial intelligence in computer networks with a view to providing references for effective optimisation of computer networks. © 2023 SPIE.

关键词： Expert systems

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Multi-Authority Attribute-Based Searchable Encryption in Cloud Storage 11

Multi-Authority Attribute-Based Searchable Encryption in Clo...

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11th IEEE international conference on computer science and Network technology, ICCSNT 2023

作者： Gong, Qinghua Zhang, Jinnan Liu, Yang Wang, Xinmin Wei, Zheng School of Electronic Engineering Beijing University of Posts and Telecommunications Beijing China School of Automation Beijing Institute of Technology Beijing Institute of Astronautical Systems Engineering Beijing China

ISBN: (纸本)9798350311594

Ciphertext policy attribute-based encryption (CP-ABE) has been widely used as a fine-grained access control mechanism for data sharing. Existing research on CP-ABE schemes in cloud computing environment predominantly focuses on a single attribute authority, which may lead to high computation overhead or a single point of failure. Besides, the encrypted data stored in the cloud restricts ciphertext retrieval. Therefore, we propose a multi-authority attribute-based searchable encryption scheme in cloud storage called MASEP for sharing data securely. In addition, the MASEP scheme supports the validity of retrieving user attributes before decryption, reducing the unnecessary computation cost. Finally, the experiment results show that MASEP scheme is proved to be IND-CPA secure under the chosen plaintext attack, and it is more efficient and promising. © 2023 IEEE.

关键词： Cloud storage

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Second-order Consensus in Discrete-time Multi-agent Systems with Reference States 2

Second-order Consensus in Discrete-time Multi-agent Systems ...

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2nd Asia conference on Electrical, Power and computer Engineering, EPCE 2023

作者： Tan, Aiguo Ju, Changjiang Yang, Yuping Chen, Chongyu Jin, Guobiao University of Shanghai for Science and Technology Public Experiment Center Shanghai China Shanghai Jiao Tong University Ningbo Artificial Intelligence Institute Department of Automation Zhejiang China Consinee Group Co. Ltd Zhejiang China

ISBN: (纸本)9798350310818

In this work, the second-order consensus in discrete-time multi-agent system (MAS) with reference states in which only a part of agents have access to is researched. According to the proposed network topology, it is unnecessary to utilize a spanning tree in the directed graph. First, three different protocols are adopted to demonstrate three typical cases on reference states. Then, necessary sufficient conditions to achieve the required consensus with reference states are derived in MASs. At last, several examples are calculated to verify the proposed theory. © 2023 IEEE.

关键词： Multi agent systems

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