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检索条件"任意字段=IEEE Conference on Automation Science and Engineering"

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FC-YOLO: A High-Precision Sign Language Recognition Algorithm Based on Global and Local Feature Collaborative Learning 6

FC-YOLO: A High-Precision Sign Language Recognition Algorith...

引用

6th International conference on Frontier Technologies of Information and Computer, ICFTIC 2024

作者： Mo, Taiping Zhou, Xudong Zhang, Xiangwen Sun, Peng School of Electronic Engineering and Automation Guilin University of Electronic Technology Guangxi Guilin541004 China Key Laboratory of Intelligence Integrated Automation in Guangxi Universities Guilin541004 China

ISBN: (纸本)9798331541750

Sign language recognition is a crucial communication tool for individuals who are deaf or hard of hearing, with its accuracy and efficiency directly impacting their daily interactions. However, existing sign language recognition models often rely heavily on global features while paying insufficient attention to subtle local details. This can decrease recognition accuracy in practical applications, ultimately hindering effective communication. To address this issue, we propose FC-YOLO, a sign language recognition algorithm that integrates collaborative learning of both global and local features. In this network, Frequency Adaptive Dilated Convolution (FADC) is employed to dynamically adjust the receptive field, effectively capturing high-frequency information and significantly enhancing sensitivity to local details. Additionally, a Cross-layer Convolution and Attention Mechanism Feature Fusion Module (CAFM) is embedded, enabling complementary integration of global semantic information and regional features, thus providing a solid foundation for recognizing complex sign language symbols. On the American Sign Language (ASL) dataset, this method achieves 97.2% accuracy, 93.3% precision, and 99.5% mean average precision. © 2024 ieee.

关键词： Semantics

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Investigating Wireless Communication's Potential for Enhancing Automated Systems in Manufacturing Process 10

Investigating Wireless Communication's Potential for Enhanci...

引用

10th ieee Uttar Pradesh Section International conference on Electrical, Electronics and Computer engineering, UPCON 2023

作者： Raman, Ramakrishnan Joon, Rakesh Kumar Kumar, Keerthipati. Singh, Rajesh Saini, Dimple Gor, Mehul Maharashtra Pune India Ganga Institute of Technology and Management Ece HaryanaKablana Jhajjar India University of Technology and Applied Science Department of Information Technology Al Mussnna Oman Uttaranchal Institute of Technology Uttaranchal University India Pune India Parul University Department of Piet India

ISBN: (纸本)9798350382471

This study looks into the means by which wireless communication technology could revolutionize the way factory automation procedures are done. It examines the drawbacks of conventional wired systems and the advantages of wireless technologies like 5G, Bluetooth Low Energy, as well as Industrial Wi-Fi. The paper describes a step-by-step implementation method, from network architecture through security measures, using Cisco Packet Tracer as a simulation tool. Examinations of scalability, and interaction with older systems, including real-time data monitoring are also done. The study shows the significance of adhering to regulatory requirements and the potential for future improvements through new technology. This research teaches manufacturers about the revolutionary potential of wireless communication, resulting in enhanced efficiency, flexibility, including competitiveness. It does this by offering real-world insights and resolving issues. © 2023 ieee.

关键词： Cisco Packet Tracer Emerging Technologies Industrial Wi-Fi Manufacturing automation Wireless Communication

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Teleoperation System of Autonomous Underwater Vehicle Toward Human-on-the-Loop: Design and Implementation 13

Teleoperation System of Autonomous Underwater Vehicle Toward...

引用

13th ieee International conference on CYBER Technology in automation, Control, and Intelligent Systems, CYBER 2023

作者： Gao, Tianming Yan, Jing Yang, Xian Hua, Changchun Guan, Xinping Institute of Electrical Engineering Yanshan University Qinhuangdao066004 China School of Electronic Information and Electrical Engineering Shanghai JiaoTong University Shanghai200240 China

ISBN: (纸本)9798350315196

The autonomou underwater vehicle (AUV) is an essential tool for exploring the ocean. However, the harsh marine environment makes full autonomy control unable to perform complex tasks. This paper employs Human-on-the-Loop (HOTL) to design an underwater teleoperation system, mainly including master human operator, buoy, slave AUV and communication network. Based on this, an integral reinforcement learning (IRL) based teleoperation controller is developed, through which operator can remotely determine the motion of slave AUV via the master unit. Finally, simulation and experiments with different scenarios both verify the effectiveness of our solution. © 2023 ieee.

关键词： Autonomous underwater vehicles

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Fault Diagnosis and Analysis of Hydraulic System Based on Partial Least Squares Method 3

Fault Diagnosis and Analysis of Hydraulic System Based on Pa...

引用

3rd International conference on Electrical engineering and Mechatronics Technology, ICEEMT 2023

作者： Wang, Xiaoming Xiong, Rui Gao, Jiashan Wang, Xingjian Beijing Institute of Aerospace Systems Engineering Beijing100076 China Beihang Umiversity School of Automation Science and Electrical Engineering Beijing100191 China

ISBN: (纸本)9798350303698

The hydraulic system is widely used as power mechanism and actuation system in large-scale industrial equipment. The strong coupling between system circuits and different fault mechanisms make fault diagnosis difficult. In order to address these issues, a fault diagnosis method based on partial least squares is proposed for hydraulic system. The AMESim simulation platform is used to simulate the fault status of hydraulic components, generate fault data, and combine partial least squares to establish a regression equation between process variables and fault types for discriminative analysis of hydraulic system fault types. The simulation results indicate that the partial least squares method can achieve process variable data fusion, extract fault features, and complete the detection, separation, and recognition of fault types. © 2023 ieee.

关键词： Failure analysis

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VTFL: A Blockchain Based Vehicular Trustworthy Federated Learning Framework 6

VTFL: A Blockchain Based Vehicular Trustworthy Federated Lea...

引用

6th ieee Information Technology, Networking, Electronic and automation Control conference, ITNEC 2023

作者： Li, Aojie Chang, Xing Ma, Jingxiao Sun, Shousheng Yu, Yantao Tongji University School of Electronic and Information Engineering China

ISBN: (纸本)9781665460033

With the rapid development of 5G and Internet of Vehicle (IoV) technology, vehicles require a mass of data-sharing to ensure the traffic safety and improve user's driving experience. However, the traditional way of sharing the original data leads to inefficient communication and the risk of privacy leakage when data leaves the vehicle's local-storage. The recent advances of privacy-preserving Federated Learning (FL) bring a solution to these challenges, which allows to train models locally based on user's data and only transmit the parameters with the raw data. But the lack of identity management in the dynamic topology of vehicles makes the FL's training process vulnerable to be attacked by malicious vehicles, which spoilages the accuracy of the global model seriously. Therefore, how to ensure the security of the FL process has become a crucial challenge. In our work, we propose a trustworthy FL framework based on blockchain, which relies on consensus mechanism to ensure safe aggregation of models, and uses digital signatures to ensure the traceability of malicious vehicles and prevent the malicious vehicles from doing harm again. Our experiment results show that the proposed scheme effectively improves the precision of global model in the malicious scene and the efficiency of model convergence. © 2023 ieee.

关键词： Blockchain

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An Infrared and Visible Image Fusion Network Based on Frequency Domain Information Extraction 25

An Infrared and Visible Image Fusion Network Based on Freque...

引用

25th ieee China conference on System Simulation Technology and its Application, CCSSTA 2024

作者： Hou, Xinhao Xue, Yanan Yang, Sen Tianjin University of Technology School of Electrical Engineering and Automation Tianjin China

ISBN: (纸本)9798350366600

The objective of infrared and visible light image fusion is to integrate data from distinct sensors to generate a more comprehensive and accurate representation of a scene. In this study, we introduce FDFusionNet, a fusion framework based on frequency domain information extraction. FDFusionNet effectively preserves thermal targets from infrared images, as well as texture structures and background details from visible images. The framework segments the extracted image features into spatial domain feature extraction and frequency domain feature extraction for enhanced performance. Fourier transform facilitates the extraction of amplitude and phase components in the frequency domain, integrating background information, while spatial domain features are extracted using SEDense. This paper achieves a balance between global and local information through the complementary nature of frequency and spatial domain features. Moreover, we incorporate information entropy to design different modal weights, effectively controlling the input ratios and suppressing redundant information and noise. Extensive qualitative and quantitative experiments demonstrate that our fusion algorithm effectively balances texture and structural information, outperforming other fusion methods on the TNO public dataset. Our method consistently ranks among the top four across various evaluation metrics on TNO data, validating its superior performance in infrared and visible light fusion scenarios. © 2024 ieee.

关键词： Frequency domain analysis

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An example study of applications based on multiple machine learning algorithms 6

An example study of applications based on multiple machine l...

引用

6th ieee International conference on automation, Electronics and Electrical engineering, AUTEEE 2023

作者： Hao, Entao Zhou, Jiajun Zhang, Hao North China Institute of Science and Technology College of Science Langfang China North China Institute of Science and Technology School of Computer Science Langfang China

ISBN: (纸本)9798350305623

This study aims to highlight the effectiveness and feasibility of multiple machine learning algorithms in solving real-world problems by comparing their application examples. The team collected data related to the research problem and utilized the XGBoost model to eliminate feature variables with low contribution rates. Subsequently, K-Means clustering and principal component analysis were used for dimensionality reduction to filter out the most important indicators that are most relevant to the prediction ability, including AALa5GearSelUp,50_Pi5ch,50_Pi5chRa5e,Min(Pi5ch)5O5oG 1, 50_5emp, and 5ime_G25oG1. Based on these metrics, the research team constructed several models such as Decision Tree, Random Forest, XGBoost, BP Neural Network and Catboost, and conducted model evaluation. Comparison results show that the XGBoost model performs best in assessing the index scores, with an accuracy rate of 0.737, a recall rate of 0.764, a precision rate of 0.791, and an F1 score of 0.866. Therefore, in summary, the XGBoost model is chosen for the best assessment of prediction ability. The algorithm is able to predict and categorize data more accurately with high prediction accuracy and model reliability. The contribution of this study is to highlight the effectiveness of machine learning algorithms in real-world problems and the fact that such models have potential and value in solving real-world problems. These models can provide quantitative assessment results and can help related fields and organizations make more accurate decisions. By comprehensively considering multiple metrics, future research can further explore and improve the algorithm to achieve better results in a wider range of application areas. © 2023 ieee.

关键词： Feature selection k-means clustering Machine learning models Principal component analysis

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CDD-YOLOv8: A Small Defect Detection and Classification Algorithm for Cigarette Packages 13

CDD-YOLOv8: A Small Defect Detection and Classification Algo...

引用

13th ieee International conference on CYBER Technology in automation, Control, and Intelligent Systems, CYBER 2023

作者： Zhu, Liming Zhang, Jun Zhang, Qiang Hu, Hongtao HangZhou Cigarette Factory of China Tobacco Zhejiang Industrial Company Limited Hangzhou China College of Control Science and Engineering Zhejiang University Hangzhou310027 China

ISBN: (纸本)9798350315196

In order to ensure the quality of cigarette products, it is significant to conduct real-time detection and classification for defects on cigarette packages in high-speed assembly line. Most industrial anomaly detection methods can only detect anomalies by modeling normal data distribution, lacking the ability to realize the fine-grained classification of anomalies, which is indispensable for reducing defective products and thus lower production costs. To solve the problem of detecting and classifying small defects in cigarette packaging, we introduced a Cigarette Defect Detection YOLOv8 algorithm (CDD-YOLOv8). By adding a small object detection head and Convolutional Block Attention Module(CBAM), our proposed model achieved better utilization of multi-level features to assist in small defect detection, contributing to better detection performance in our cigarette dataset. © 2023 ieee.

关键词： Defects

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De-Biasing user conformity bias and item popularity bias in Group recommendation 6

De-Biasing user conformity bias and item popularity bias in ...

引用

6th ieee Information Technology, Networking, Electronic and automation Control conference, ITNEC 2023

作者： Jia, Junjie Shang, Tianyue Li, Lifang Chen, Si Northwest Normal University College of Computer Science and Engineering Lanzhou China

ISBN: (纸本)9781665460033

The recommendation system is usually faced with the problem of popularity bias, and the collected interactive data often presents quite unbalanced or even long-tail ***, most of the existing studies have considered how to eliminate the negative effects brought by the popularity bias, thus ignoring the two sides of the popularity *** the item level, people tend to comment on popular items. So is it all positive? Most research on popularity bias has focused on the conformity behavior and has increased the diversity of personal recommendation lists. At the user level, does everyone want to pursue the preferences of the mainstream group? The reported user responses are skewed toward popular items rather than users' true interest. We believe that not all popularity bias are harmful. In addition to the consistency effect, the uneven distribution of items can be attributed to the diversity of items' quality. To address this problem, we propose a new de-biasing mechanism, which uses user conformity bias and item popularity bias to improve the accuracy of recommendation. © 2023 ieee.

关键词： Conformity bias Fairness Group recommendation Popularity bias

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Research on Control Strategy of PMSM for Electric Vehicles Based on Nonlinear Model 5

Research on Control Strategy of PMSM for Electric Vehicles B...

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5th ieee Advanced Information Management, Communicates, Electronic and automation Control conference, IMCEC 2022

作者： Li, Xuerong Song, Wenxiang College of Mechanical and Electrical Engineering Donghai Vocational and Technical College Shanghai China School of Mechatronics Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9781665479677

In actual operation, the performance of PMSM used in electric vehicle and its drive system is greatly affected by magnetic circuit saturation and cross-saturation, and the traditional linear model can no longer meet the requirements of high-precision and high-performance control systems. The nonlinear model of vehicle permanent magnet synchronous motor based on finite element is established, the influence of motor parameters on the control algorithm is analyzed, the current loop decoupling control based on the table lookup method is proposed, The simulation results show that the motor control system considering the nonlinear model can adapt to different operating conditions and output the maximum torque, and has good speed dynamics and anti load disturbance performance. © 2022 ieee.

关键词： Magnetic circuits

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