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检索条件"任意字段=7th International Conference on Computer and Information Processing Technology, ISCIPT 2022"

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R-Wave Detection Algorithm Based on Central Difference and Adaptive Multi-threshold 7

R-Wave Detection Algorithm Based on Central Difference and A...

引用

7th international conference on computer information Science and Application technology, CISAT 2024

作者： Xu, Ke Wang, Huibin Guo, Sikai Chen, Wenping Hohai University Hhu College of Information Science and Engineering Nanjing China

ISBN: (纸本)9798350375107

As a non-invasive method for diagnosing heart diseases, electrocardiography (ECG) relies on R-wave detection as a foundational step for other ECG waveform analysis. To further meet the demands for accuracy and real-time detection of R-waves in automatic ECG analysis, this paper proposes a low-complexity, fast, and reliable real-time R-wave detection algorithm. An R-wave detection method based on central difference and adaptive multi-threshold is designed. First, this paper proposes the use of central difference for R-wave enhancement, effectively improving the detection capability for low amplitude and low slope R-waves. Secondly, an adaptive multi-threshold strategy is proposed, which adaptively adjusts the current detection threshold based on the detected R-wave amplitude and RR interval, making it suitable for R-wave detection in cases of sudden changes in RR interval and R-wave amplitude. the proposed algorithm's performance was evaluated using ECG signals from the MIT-BIH database, achieving an overall sensitivity, positive predictive value, and detection error rate of 99.73%, 99.82%, and 0.46%, respectively. the processing time for a 30-minute ECG recording is approximately 0.52 seconds. the results indicate that the algorithm is accurate, efficient, and suitable for real-time automatic ECG analysis. © 2024 IEEE.

关键词： Shear waves

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A Design of Data Acquisition and Monitoring System for Intelligent Electrical Cabinets 7

A Design of Data Acquisition and Monitoring System for Intel...

引用

7th international conference on computer and information processing technology, iscipt 2022

作者： Jiang, Yuji Yang, Yongjie School of Information Science and Technology Nantong University Nantong China

In modern industrial age, the use of electric energy has a higher status in the production and operation of enterprises. In order to ensure the safe and stable operation of the power distribution cabinet in the power distribution room, and to improve the repair accuracy of the staff when an error occurs. this paper designs a monitoring system that collects the internal status data of the power distribution cabinet. this design is based on the STM32 of ARM Company, which can control modules to collect various kinds of data such as voltage and current, temperature and humidity, smoke concentration, etc. then upload the data to the monitoring cloud platform through 4G Cat1 module. the user can monitor the status on the WeChat applet. When the data is abnormal, the terminal automatically alarms and sends a short message to the control personnel, so that the staff can quickly fix the machine and reduce the economic loss of the enterprise. © 2022 Copyright for this paper by its authors.

关键词： Data acquisition

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Research on Differential Privacy Protection of Power Grid Data Based on Artificial Intelligence and Federated Learning 7

Research on Differential Privacy Protection of Power Grid Da...

引用

7th IEEE international conference on information Systems and computer Aided Education, ICISCAE 2024

作者： Zhang, Zhao Wu, Fan Jiao, Wentao State Grid Info & Telecom Co. Ltd. Beijing China China-power Information Technology Co. Ltd. Beijing China

ISBN: (纸本)9798350350760

With the rapid growth and intelligent development of power grid data, privacy protection of this data has become a pressing issue. this paper proposes a differential privacy protection method based on artificial intelligence and federated learning to address the privacy protection needs of power grid data. First, the basic concepts and related research results of differential privacy and federated learning are reviewed, and the advantages and disadvantages of existing power grid data privacy protection schemes are analyzed. then, a privacy protection system combining differential privacy and federated learning technologies is designed and implemented, including modules for data processing, model training, and privacy protection mechanism integration. Experiments on real power grid datasets verify that this system can effectively improve the accuracy of data analysis and model training while ensuring data privacy. the experimental results show that this method can effectively protect the privacy of power grid data and perform well in various application scenarios. Finally, this paper discusses the prospects of this method in practical applications and future research directions. ©2024 IEEE.

关键词： Federated learning

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Research on 3D reconstruction technology based on the fusion of polarization imaging and light field depth information 7

Research on 3D reconstruction technology based on the fusion...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Yuan, Lin Gao, Jun Wang, Xin Cui, Hao Hefei University of Technology School of Computer and Information Hefei China

ISBN: (纸本)9781665478571

For objects with smooth surface and single texture, the traditional reconstruction algorithm cannot accurately recover the ideal results. the research shows that the shape features of the measured object can be recovered more accurately by using polarization information in the reconstruction process. However, due to the ambiguity of the azimuth of the surface normal, it is difficult to obtain the accurate depth information directly. Referring to the depth information image provided by the light field camera, this paper designs a depth imaging system mixed by the polarization camera and the light field camera. the depth information obtained by the light field camera is used to guide and eliminate the ambiguity of the normal vector of the polarization surface, so as to achieve higher accuracy in the three-dimensional surface reconstruction of the object. the experiment and analysis show that the relative error between the reconstructed target surface and the real target surface is less than 10%. © 2022 IEEE.

关键词： Cameras

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An Improved Lightweight Human Normative Pose Estimation Algorithm 7

An Improved Lightweight Human Normative Pose Estimation Algo...

引用

7th international conference on computer information Science and Application technology, CISAT 2024

作者： Li, Danyu Ma, Yunci Zou, Jiajun Xu, Zhiming Guangzhou Xinhua University School of Information and Intelligent Engineering Dongguan China The Fifth Affiliated Hospital Southern Medical University Division of Nephrology Guangzhou China

ISBN: (纸本)9798350375107

Human pose estimation algorithms have high accuracy and speed, but there are still issues of missed and false detections. this article proposed a lightweight human normative posture estimation algorithm for precise target positioning and action norm evaluation in human normative posture recognition. First, the YOLOv4 object detection algorithm and the lightweight OpenPose algorithm were combined to obtain target bone node data. Second, by calculating action angles as features for extraction, an action matching method was constructed to evaluate and correct the training actions. Finally, the extracted training action skeleton image was trained and classified using a deep convolutional neural network (DCNN) model. Relieved the uncertainty and irregularity of human normative movements. Training and validation were conducted on the collected datasets of professional coaches, and the experimental results shown that, our model achieved better performance than other models. © 2024 IEEE.

关键词： Convolutional neural networks

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TransSnake: Contour-Based Wild Animal Instance Segmentation Using Contour Transformer 7

TransSnake: Contour-Based Wild Animal Instance Segmentation ...

引用

7th international conference on Pattern Recognition and Artificial Intelligence, PRAI 2024

作者： Liu, Tong Zhang, Zheng Wu, Zedong Zheng, Bochuan School of Computer Science China West Normal University Nanchong China School of Mathematics & Information China West Normal University Nanchong China School of Computer Science Institute of Artificial Intelligence China West Normal University Nanchong China

ISBN: (纸本)9798350350890

Wild animal instance segmentation technology plays a significant role in wild animal research, enabling automatic wild animal information extraction, improving data processing speed, and reducing researcher burden. Inspired by the Snake algorithm and Transformer, we propose TransSnake, a new contour-based instance segmentation model. Its process included three stages: initial contour, coarse contour, and refined contour. In the coarse contour stage, we introduce a multi-scale fusion module to fuse multi-scale contour information, expand the receptive field, and generate a higher-quality coarse contour. the obtained coarse contour lays a solid foundation for subsequent contour refinement. However, relying solely on local information for contour deformation can result in substantial prediction errors. therefore, we adopt the contour transformer in the refined contour stage to capture global information among contour points. this module uses global information to guide contour deformation and improve segmentation accuracy. Experimental results illustrate the outstanding performance of our method on the LoTE-Animal dataset and validate the feasibility of contour-based instance segmentation methods in wild animal segmentation. Meanwhile, the excellent performance is also shown from our approach on the SBD dataset. © 2024 IEEE.

关键词： Contourlet transform

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Research on an Adaptive RRT Path Planning Algorithm Based on Regional Sampling 7

Research on an Adaptive RRT Path Planning Algorithm Based on...

引用

7th international conference on computer information Science and Application technology, CISAT 2024

作者： Su, Yu Li, Hongbing Gong, Wenbin Chen, Honghao Jiang, Yutao Long, Boxuan Chongqing Three Gorges University College of Computer Science and Engineering Chongqing Wanzhou China Chongqing Three Gorges University College of Electronic and Information Engineering Chongqing Wanzhou China Changchun University of Science and Technology College of Computer Science and Technology Jilin Changchun China

ISBN: (纸本)9798350375107

An enhanced RRT path planning algorithm based on regional sampling is proposed with the goal of addressing the issues of inadequate guidance, discontinuous sampling, and unsatisfactory path in RRT algorithm path search in complicated situations. the improved algorithm first enhances the algorithm's guidance and avoids unnecessary sampling by using a target bias strategy and a regional sampling strategy. Secondly, an adaptive step size strategy based on obstacle factors is adopted to dynamically adjust the step size by detecting the complexity of the environment around the expansion direction. Finally, the produced path is trimmed and optimized. According to simulation results, the revised algorithm reduces running time, path length, and number of path nodes by 68.65%, 18.56%, and 85.45%, respectively, in comparison to the RRT algorithm. the enhanced approach reduces the running time, path length, and number of path nodes by 14.06%, 12.91%, and 82.97%, respectively, in comparison to the Bias RRT algorithm. © 2024 IEEE.

关键词： Signal sampling

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Construction and Application of Subject Knowledge Graph for Basic Education 7

Construction and Application of Subject Knowledge Graph for ...

引用

7th international conference on computer and information processing technology, iscipt 2022

作者： Xu, Tao Ma, Xiaqing Wang, Fengsi Liu, Chun Zhang, Zixiang Lu, Peiming Han, Daojun Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China School of Computer and Information Engineering Henan University Kaifeng475004 China Henan Technology Innovation Center of Spatio-Temporal Big Data Henan University Zhengzhou450046 China Henan Industrial Technology Academy of Spatio-Temporal Big Data Henan University Zhengzhou450046 China

In view of the problem that the distribution of knowledge points in the current knowledge system in the form of chapters can no longer meet the needs of students and teachers. this paper proposes to use SVM to identify knowledge points of tests, build a subject Knowledge Graph based on the identified knowledge points, and design and implement a subject Knowledge Graph system. this paper takes the mechanical movement of the first chapter of the eighth grade (upper) physics course as an example to conduct empirical research. By 10-fold cross-validation, the average F1 value of the algorithm used in this paper is 89.66%. © 2022 Copyright for this paper by its authors.

关键词： Knowledge graph

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Research progress and trend analysis of object tracking technology based on CiteSpace 7

Research progress and trend analysis of object tracking tech...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Yu, Liang Qingdao University of Technology School of Information and Control Engineering Qingdao China

ISBN: (纸本)9781665478571

Object tracking technology is an important research direction in the field of computer vision, and nowadays, it has played an increasingly indispensable role in the fields of intelligent surveillance, modern military, human-computer interaction, intelligent transportation, etc. While making breakthroughs, it has also brought great convenience to people's lives. In this paper, CiteSpace information visualization software is used to visualize the object tracking research literature based on nearly 10,000 papers in the field of object tracking from 2001 to 2021. From the bibliometric perspective, the visual knowledge graphs of information on three aspects of object tracking technology: scientific cooperation, research fields, and recent progress are analyzed, in which the analysis of scientific cooperation includes the distribution of countries and institutions, the analysis of research fields includes the distribution of categories and keywords, and the analysis of recent progress and frontiers includes the distribution of references and the analysis of keyword timeline graph. then, we present the three main problems and challenges facing this technology: changes of illumination and color, changes of scene and posture, and the distinction between foreground and background. And three targeted suggestions are proposed for feature fusion, 3D reconstruction, and deeper development based on Siamese Network in deep learning algorithms. Finally, the future development of object tracking technology has been prospected. © 2022 IEEE.

关键词： computer vision

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MFRIN: Rotation-Invariant Network with Multi-feature Fusion of Point Cloud 7

MFRIN: Rotation-Invariant Network with Multi-feature Fusion ...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Li, Shuyu Zhang, Xudong Hefei University of Technology School of Computer and Information Hefei China

ISBN: (纸本)9781665478571

Point cloud carries rich geometric information and has unique advantages in computer vision field. Existing methods can effectively identify objects in a fixed perspective, but in practical, the object direction is unknown, which greatly affects the accuracy of the network. In this paper, we propose a pre-network based on ellipsoid fitting algorithm to extract rotation invariant features of point cloud. We design a two-branch network to mine features at different levels. In the first branch, we feed the rotation invariant feature to PointNet-based backbone to learn global feature;in the side branch, we use knn to transform the point cloud into a graph structure and apply attention model to extract more discriminative local features. We show that MFRIN can extract rotation-invariant representations for point cloud without data augmentation, and achieves best performance than state-of-the-art methods on rotating point clouds. © 2022 IEEE.

关键词： computer vision

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