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

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Distributed Robust Particle Filter Based on Wasserstein Metric 3

Distributed Robust Particle Filter Based on Wasserstein Metr...

引用

3rd international conference on computer, Control and Robotics, ICCCR 2023

作者： Wang, Hao Yang, Aolei Sun, Qing School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9781665492126

In this paper, for nonlinear systems with uncertain interference factors, particle filter can no longer accurately estimate the state when both process noise and measurement noise are unknown, so a distributed robust particle filter method based on Wasserstein metric is proposed. The method mainly uses Wasserstein metric to construct the fuzzy set of real data distribution, replaces the original empirical distribution with the prior estimation distribution of particle filter, and takes it as the center point of the new fuzzy set;Secondly, on the premise of tolerable conservatism, the optimal state estimator in this state is constructed according to the criterion of minimum root mean square error in the worst case;Then, the updating and resampling of particle filter are used to complete the calculation of a posteriori estimation, which solves the problem of state estimation of nonlinear systems under uncertain disturbances;Finally, an example is given to verify the feasibility and effectiveness of the distributed robust particle filter method. © 2023 IEEE.

关键词： State estimation

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Construct and Analysis of Metal Cutting Tool Remanufacturing Service Model 6

Construct and Analysis of Metal Cutting Tool Remanufacturing...

引用

6th international conference on computer Network, Electronic and automation, ICCNEA 2023

作者： Zhu, Ziyan Cao, Yan Fu, Leijie Dong, Chaoyi Xi'an Technological University School of Mechatronic Engineering Xi'an710021 China Xi'an Technological University School of Computer Science and Engineering Xi'an710021 China

ISBN: (纸本)9798350305388

Manufacturing is the pillar industry of the national economy, and remanufacturing is an important direction for the manufacturing industry to move towards greening, but the current research lacks a macro analysis of the tool service model. Given this problem, this paper first analyzes the current situation of metal cutting tool remanufacturing service mode. Then, the cause and effect analysis of the remanufacturing service model was carried out through Vensim PLE software. Finally, based on the above analysis, the remanufacturing service model is qualitatively analyzed and improvement strategies are proposed, which can promote the sustainable development of the tool remanufacturing market and increase the corresponding service revenue. © 2023 IEEE.

关键词： Metal cutting

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Design and implementation of football training system based on computer vision technology 7

Design and implementation of football training system based ...

引用

7th international conference on Electronic Information technology and computer Engineering (EITCE)

作者： Gao, Hongfei Meng, Shasha Ma, Shaowen Chongqing Three Gorges Vocat Coll Chongqing 404100 Peoples R China

ISBN: (纸本)9798400708305

In order to improve the science and quality of football training, a football training system based on computer vision technology is studied. Collect initial motion data through motion capture to form an action database, modify and design the actions in the action database, obtain standard technical actions, and arrange and simulate each standard technical action through motion splicing;By using video shooting technology to obtain the image data of athletes during physical exercise, the measurement deviation in sports training is discussed through the trajectory tracking and error judgment of the motion nodes, so as to provide more efficient sports guidance and improve the movement and training level. The simulation test results show that compared with other corresponding systems, the system is outstanding in the aspects of fast response and improved control accuracy, so as to realize the optimal monitoring effect of sports training errors.

关键词： Sports training computer vision technology Image processing

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Tracking and Security Features Enhancement in a Smart School Bus Using IoT

Tracking and Security Features Enhancement in a Smart School...

引用

2023 international conference on IoT, Communication and automation technology, ICICAT 2023

作者： Abhay Surya, R.L. Likith, A.S. Guruprasad, N. Global Academy of Technology Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350302820

Public transportation systems are often not taken into account by the parents as a mode of transport, due to the risks and lack of safety measures they possess. The Internet of Things (IoT) based applications and devices implemented in these School buses, rectify the concerns amongst the parents to have a trustworthy infrastructure. The system provides a solution to meet safety requirements by consistent student tracking using RFID and GPS technologies to report boarding and deboarding time of the student passing through 2 checkpoints, real-time bus location, and speed tracking to abide by the rules. Furthermore, a dual authentication to confirm that no unauthorised person can access the bus system, and surveillance IP camera for indoor monitoring. Sensors like Door sensors and Proximity sensors connected to Arduino Uno are used to mark the onboard and post-deboarding safety to depict a child's presence in the red zones, respectively. This can nullify or drastically bring down the occurrence of any undesirable instances. A mobile application displaying all the necessary information is made available for the ease of parents. Overall, the proposed system can uplift the safety of school children while travelling, providing parents with a stress-free and worriless environment. © 2023 IEEE.

关键词： Radio frequency identification (RFID)

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Audio Assist: Enabling Object Detection Through Speech for the Visually Impaired 2

Audio Assist: Enabling Object Detection Through Speech for t...

引用

2nd international conference on automation, Computing and Renewable Systems, ICACRS 2023

作者： Shanmugapriya, S. Priya, Gondipalli Hari Sai, Dola Lokesh Jethin, Gogineni Kumar, Chintamani Vinod Department of Computer Science and Engineering Kalasalingam Academy Of Research And Education Tamilnadu Virudhunagar India

ISBN: (纸本)9798350340235

Object detection based on deep learning is an essential application in deep learning technology, which is distinguished by its superior feature learning and feature representation capabilities when compared to traditional object identification approaches. Generally, the normal people can identify where the objects are located easily but it’s not that easy for visually impaired people to identify the objects and its location. Also, it is very challenging to create a computer model to identify the objects. Actually, the object detected will be appear on the screen but it’s not useful for visually impaired that’s why we are using Audi Assist which helps us toconvert text to speech. And we are enabling the audio assist technology to gives the audio output after identifying the object. And it describes where the object is it located. This study utilizes a largedataset of objects like mobiles,water bottle, cups and many more. This model is not only trained to detect objects also detects persons. This technology has enormous promise for increasing the freedom and safety of visually impaired people by allowing them to explore and interact with their surroundings more confidently and efficiently. It is a big step towards inclusion and accessibility in our quickly expanding technology ecosystem. The objectsdetected are translated into meaningful audio cues, providing immediate to user. © 2023 IEEE.

关键词： Architecture Audio Assist computer Vision Deep Learning Object Classification Segmentation YOLO (You Only Look Once)

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A method for estimating the contribution of an object to scene semantics 4

A method for estimating the contribution of an object to sce...

引用

4th international conference on computer Vision and Information technology, CVIT 2023

作者： Lin, Zhiyuan Zhu, Feng Wang, Jianyu Wang, Qun Zhao, Pengfei Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Faculty of Robot Science and Engineering Northeastern University Shenyang110169 China

ISBN: (纸本)9781510672864

The amount of semantic contribution of each object in an image to understand the scene is different. Understanding the relative importance of objects in a scene for scene semantics is critical for various computer vision applications, such as scene recognition and image captioning. In this paper, we refer to the contribution of an object to scene semantics as the degree of its gist and propose a method for Estimating the degree of the Gist of an Instance (EGoI). In the EGoI method, an object gist degree is estimated by the semantic features comparison strategy and the semantic distance comparison strategy. In the first strategy, the image is represented as a scene graph first, then the aggregation features and the node features of different graph node combinations are calculated to estimate the instance gist that is not in the combination of the nodes. In the second strategy, the captions of the complete and incomplete images are generated, then the semantic distance of these captions is used to estimate the instance gist deleted in the scene. Different strategies for estimating the gist degree of instances are tested in the experiments. The results show that the proposed method can effectively quantify the contribution of an instance to scene semantics. Among these strategies, the method that compares semantic features has better discriminative power for the gist degree of various instances in the scene. © 2024 SPIE.

关键词： Semantics

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Mapping the Scientific Landscape of Internet of Things and Artificial Intelligence Using VOSViewer

Mapping the Scientific Landscape of Internet of Things and A...

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2023 international conference on IoT, Communication and automation technology, ICICAT 2023

作者： Soni, Tanishq Gupta, Deepali Uppal, Mudita Gupta, Gifty Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Mm Engineering College Maharishi Markandeshwar Deemed to Be University Department of Computer Science Haryana Mullana-Ambala133207 India

ISBN: (纸本)9798350302820

The Internet of Things and Artificial Intelligence are two quickly expanding disciplines that are coming together to provide everyone with exciting new prospects and help automate every industry. The Internet of Things (IoT) refers to a network of interconnected devices, sensors, and software that can communicate with each other and exchange data over the internet. Artificial Intelligence (AI) and Machine Learning (ML) algorithms are being used to analyze and predict the output. The IoT has gained significant attention in recent years due to its potential to transform various industries, including healthcare, transportation, and agriculture. The convergence of IoT and AI is opening up new possibilities in a wide range of industries and applications. Some common bibliometric measures used in IoT research include citation counts, co-citation analysis, and bibliographic coupling. Citation counts measure the number of times an article has been cited by other articles, while co-citation analysis examines the frequency of the articles. Bibliometric analysis is carried out using the most powerful tool, VOSviewer, which is widely used in the academic community for bibliometric analysis and visualization. © 2023 IEEE.

关键词： Internet of things

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A Novel Approach with Fusion Edge Prediction Strategy for Table Structure Recognition 11

A Novel Approach with Fusion Edge Prediction Strategy for Ta...

引用

11th international conference on Information Systems and Computing technology, ISCTech 2023

作者： Liu, Yingli Zhang, Guangtao Shen, Tao Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650093 China Kunming University of Science and Technology Yunnan Key Laboratory of Computer Technologies Application Kunming650500 China

ISBN: (纸本)9798350342406

Table, as an information carrier with high information density and direct display form, are widely used in scientific literature and social production documents. Accurately identifying tables from various documents will significantly promote the intelligent application of documents. The table's structural information is crucial for comprehending how the text content in the table relates to one another, but teaching a computer to fully understand a table's structure is still a very difficult undertaking. In this research work, we provided a unique edge-based method to recognize table structures. Specifically, we define the inter-cell relationships as an edge prediction problem and leverage graph convolutional networks to learn representations of the cells. These learned representations are then utilized to directly predict the connections between the cells. The experimental results conducted on three publicly available datasets for table structure recognition provide compelling evidence supporting the feasibility and usefulness of our presented methodology. © 2023 IEEE.

关键词： Forecasting

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Earthquake big data processing and visualization based on PyEcharts 3

Earthquake big data processing and visualization based on Py...

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3rd international conference on Artificial Intelligence, automation, and High-Performance Computing, AIAHPC 2023

作者： Wu, Jiandong Wang, Qiang Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System East China University of Technology Nanchang China Software School of East China University of Technology Nanchang China

ISBN: (数字)9781510666580

ISBN: (纸本)9781510666573

This paper mainly uses the Python language and the pyecharts library to mine the earthquake data that occurred around the world in 2020, and finally displays it with pie charts, bar charts and other graphics. It lays a foundation for better use and processing of earthquake big data in the future, and also demonstrates the application of big data in other industries. © 2023 SPIE.

关键词： Visualization

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A Study of Task Offloading Strategies in IoV 6

A Study of Task Offloading Strategies in IoV

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6th international conference on computer Network, Electronic and automation, ICCNEA 2023

作者： Wei, Jingyun Liang, Xiangyang Xi'an Technological University School of Computer Science and Engineering Xi'an710021 China

ISBN: (纸本)9798350305388

In this paper, we study task offloading for mobile edge computing in the Internet of Vehicles (IoV). We use response time as a system performance metric and use a closed queuing network to analyze the optimal task offloading probability, which enables task offloading to have latency *** a vehicle offloads a task, there is an optimal offload probability allocation ratio so that the task has the same response time regardless of whether the task is offloaded to the cloud center or the edge layers to achieve task offload fairness. The distribution ratio to achieve fairness in task offloading is affected by the number of vehicles. Through experiments, we learn that the more vehicles there are, the more computational tasks need to be offloaded to the cloud server to achieve fairness. Also, the average response time of the edge server grows rapidly as the number of vehicles increases. © 2023 IEEE.

关键词： Vehicles

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