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intelligent recognition System of Nursing Students’ Procedural Steps of Cardiopulmonary Resuscitation Based on 3D-ResNet

Intelligent Recognition System of Nursing Students’ Procedu...

引用

Educational Technology (ICET), IEEE international conference on

作者： Yao Xiao Gaoge Wang Haimei Zhang Mengmeng Qi Qiaoling Miao Bowen Liu Faculty of Artificial Intelligence in Education Central China Normal University Wuhan China

ISBN: (数字)9798350376944

ISBN: (纸本)9798350376951

In the traditional training of cardiopulmonary resuscitation (CPR) for nurse students, teachers use observation method to evaluate students' acquisition of operation skills, which not only has high time and manpower cost, but also has strong subjectivity. the automatic recognition of CPR procedural steps is an important prerequisite for intelligent evaluation of CPR skills. therefore, an automatic recognition system of procedural steps based on 3D-Resnet is proposed for CPR training. First, this study developed an unaware data collection environment for the collection of video data during the CPR training of nurses. Secondly, based on 3D-Resnet, the intelligent recognition system of CPR procedural steps is constructed, and the functional interface of CPR procedural steps analysis report is provided for teachers and students respectively. By constructing an automatic recognition system for CPR procedural steps, the quality and efficiency of CPR training can be significantly improved, which provides a basis for intelligent evaluation in CPR training.

关键词： Training Costs Annotations Medical services Educational technology Streaming media Data collection Solids Real-time systems

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Research on the Design of intelligent Medical Interactive Robot Based on OpenMV

Research on the Design of Intelligent Medical Interactive Ro...

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Electronic Information Engineering and Computer Science (EIECS), 2021 international conference on

作者： Baicheng Pan Fan Gong Huijiong Zhan Zhengtao Liao Yajun Ou Yunyu Zhou Guangzhou Institute of Science and Technology College of Intelligent Manufacturing and Electrical Engineering Guangdong China

ISBN: (数字)9798331531409

ISBN: (纸本)9798331531416

With the continuous progress of science and technology, image and speech recognition technology has been widely used in many fields. In order to enhance the health management function of the medical interactive robot, an intelligent medical interactive robot based on OpenMV is designed in this study. the STM32 microcontroller is used as the main control, and the OpenMV camera module, speech recognition module and WIFI module are integrated. through these modules, the robot can realize image recognition, voice interaction, open the medicine box, intelligent access to drugs and other functions. At the same time, the WIFI module and the Aliyun platform are used to send and receive data to the WeChat Mini Program, and the user can remotely open the medicine box, manage the medicine and set the reminder on the applet. through a series of tests, the experimental results show that compared with the traditional medical interactive robot, the design improves the convenience and accuracy, and can facilitate the use of the elderly group to the greatest extent.

关键词： Image recognition Social networking (online) Microcontrollers Robot vision systems Speech recognition Message services Older adults Robots Wireless fidelity Biomedical imaging

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Finger Pointnet: An End-to-end Embedded Network for 3D Fingerprint Verification

Finger Pointnet: An End-to-end Embedded Network for 3D Finge...

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pattern recognition and Machine Learning (PRML), IEEE international conference on

作者： Yixin Huang Feng Liu Dongliang Yang Changjiang Song Shenzhen University Shenzhen China Heilongjiang Academy of Sciences Intelligent Manufacturing Research Institute Heilongjiang China

Contactless 3D fingerprint gains significant attention in recent years. Much of previous works for 3D fingerprint verification were based on minutiae. they required a series of laborious preprocessing and relied on software to extract minutiae. To alleviate these problems, this research presents an end-to-end embedded network for fingerprint verification. Firstly, we propose to extract ridge lines from the original large and redundant 3D fingerprint point cloud data. then, we design two weight-shared encoders to extract features from a pair of positive 3D fingerprints. Finally, loss backpropagation from the hardest sample in a mini-batch permitted in our approach makes it can distinguish negative samples. the experiments on a public database and an in-house database verify that our approach achieves desirable performance and significantly speeds up feature extraction and matching compared with traditional approaches.

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intelligent question answering system based on entrepreneurial incubation knowledge Graph 4

Intelligent question answering system based on entrepreneuri...

引用

4th international conference on pattern recognition and Artificial Intelligence, PRAI 2021

作者： Feng, Siling Chen, Hao Huang, Mengxing Wu, Yuanyuan Hainan University School of Information and Communication Engineering Haikou China

ISBN: (纸本)9781665413220

With the development of science and technology, the importance of innovation for the development of science and technology has become more and more important. In the current era of information explosion, in order to meet the needs of existing enterprises and individuals for obtaining entrepreneurial information, this system has designed an intelligent question-and-answer system based on the entrepreneurial incubation knowledge graph. the system locates the field of innovation, uses crawler software to crawl data in the field of entrepreneurial incubation to construct a knowledge graph, and uses natural language to conduct man-machine dialogue to query and solve related problems of entrepreneurial incubation. the system stores massive amounts of data in the Neo4j graph database, and uses a pattern matching algorithm to connect the natural language input by the user with the knowledge base entity to classify and query the problem. this system has special practical value in the intelligent question answering system of the knowledge graph in the field of entrepreneurial incubation. © 2021 IEEE.

关键词： Knowledge graph

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Revealing Tourist Behavior Dynamics through Network Science and Satisfaction Metrics

Revealing Tourist Behavior Dynamics Through Network Science ...

引用

Digital Society and intelligent systems (DSInS), international conference on

作者： Tengfei Shao Yuya Ieiri Haoran Luo Shenglei Li Goto Masayuki Shingo Takahashi Graduate School of Creative Science and Engineering Waseda University Tokyo Japan Graduate School of Information Production and Systems Waseda University Kitakyushu Fukuoka Japan

ISBN: (数字)9798331528829

ISBN: (纸本)9798331528836

this study introduces the Visitation pattern Analysis (VPA) Model, which integrates network motifs with satisfaction metrics to analyze tourist visitation patterns comprehensively. By employing a novel approach that combines the theoretical rigor of network science with practical tourist satisfaction indices, the model aims to enhance the strategic planning and operational efficiency of tourism routes. Utilizing data collected from tourists through field surveys and electronic tracking, the model identifies prevalent network motifs within the tourism network, revealing the patterns influencing tourist behaviors and satisfaction levels. the findings suggest that the VPA model captures complex relational dynamics and offers actionable insights for improving tourist experiences and destination management. this research contributes to tourism studies by providing a robust analytical tool that supports nuanced management and optimized route planning in the tourism industry.

关键词： Measurement Surveys Analytical models Tourism industry Network analyzers Strategic planning Network motifs Data models pattern analysis intelligent systems

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the Object Detection of Underwater Garbage with an Improved YOLOv5 Algorithm 22

The Object Detection of Underwater Garbage with an Improved ...

引用

4th international conference on pattern recognition and intelligent systems, PRIS 2022

作者： Teng, Xiaowen Fei, Yuhuan He, Kai Lu, Lihui College of Engineering Qufu Normal University China Rizhao Huilian Zhongchuang Institute of Intelligent Technology China

ISBN: (纸本)9781450396080

Litter deposition in aquatic environments has devastating effects on marine ecological environment and poses a threat to a sustainable economy. Autonomous Underwater Vehicles (AUV) could solve the issue nicely by detecting and clearing litter. A good object detection algorithm is very important in the process of AUV detection and garbage collection. In this research, YOLOv5 was applied as the detection algorithm of the detector and the prediction side of the algorithm was improved. the anchor boxes of the model are re-clustered by using the improved KMeans++ algorithm, the loss function was optimized and the box loss function of the original model was replaced by CIoU. When detecting the trash_ICRA19 dataset, the results demonstrated that the improved model achieved a detection accuracy of 88.7%, a mean average precision (mAP) of 90.6%. the mean average precision of the research work was 9.6% higher than previous studies. the results showed that the improved model could realize the detection and identification of plastic waste in water. © 2022 ACM.

关键词： Object detection

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Design and Implementation of an Image recognition System Based on the Embedded AI SOC Chip YuLong810A

Design and Implementation of an Image Recognition System Bas...

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Electronic Information Engineering and Computer Science (EIECS), 2021 international conference on

作者： Zhiguang Lei Xin'An Qiu Zhiyong Lei Zhijun Lei Lanzhou Institute of Physics Lanzhou China Beijing Racobit Electronic Information Technology Co. Ltd. Beijing China China Electronics Technology Group Corporation 58th Research Institute Wuxi China

ISBN: (数字)9798331531409

ISBN: (纸本)9798331531416

To enhance real-time image recognition capabilities, an efficient embedded image recognition system was designed using the YuLong810A chip. By optimizing the hardware platform, image preprocessing, feature extraction algorithms, and classification models, the system achieves high-precision image recognition and classification. Experimental results indicate that the system significantly outperforms traditional methods in various performance metrics, demonstrating exceptional accuracy and stability. this suggests a broad range of applications in the field of intelligent vision.

关键词： Measurement Image recognition Accuracy Stability analysis Hardware Robustness Real-time systems Classification algorithms System-on-chip Image preprocessing

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Tanks detection and recognition based on custom dataset model

Tanks detection and recognition based on custom dataset mode...

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Smart Information systems and Technologies (SIST), IEEE international conference on

作者： Vasyl Lytvyn Nazar Oleksiv Mariia Nazarkevych Lviv Polytechnic National University Lviv Ukraine

ISBN: (数字)9798350374865

ISBN: (纸本)9798350374872

this research explores the field of Artificial Intelligence vision, specifically concentrating on training a You Only Look Once (YOLO) model to recognize military objects, with a focus on tanks. Utilizing the capabilities of deep learning and YOLO’s real-time object detection, the study introduces a comprehensive methodology aimed at improving the precision and effectiveness of identifying military assets. the approach encompasses the compilation of diverse datasets, precise annotation, and the development of a customized training plan to equip the YOLO model with the capability to discern intricate features of tanks across various scenarios. through meticulous experimentation and refinement, the trained model demonstrates heightened proficiency in real-world situations, opening avenues for advancements in military surveillance, security, and strategic decision-making. the results underscore the potential of AI vision, particularly YOLO, in fortifying defense systems by enabling intelligent and swift recognition of military objects.

关键词： YOLO Training Surveillance Color Real-time systems Object recognition Time factors

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Research on the Identification Method of GIS Partial Discharge Based on VGG-16 Algorithm

Research on the Identification Method of GIS Partial Dischar...

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Energy Engineering and Power systems (EEPS), international conference on

作者： Ziyu Wan Wenbo Huang Fengrui Cheng Xixiu Wu School of Automation Wuhan University of Technology Wuhan China China Power Engineering Consulting Group Central Southern China Electric Power Design Institute co. Wuhan China

ISBN: (数字)9798350366914

ISBN: (纸本)9798350366921

Partial discharge (PD) is one of the important causes of insulation failure in GIS, and it is also an important criterion for evaluating the insulation level of GIS. Accurately identifying the type of GIS PD can effectively assist the relevant operation and maintenance personnel to carry out operation and maintenance of GIS. In order to accurately identify the type of GIS PD, this paper extracts the PRPS pattern of UHF signals from the cloud, summarizes the characteristics of the pattern, and concludes the feasibility of using convolutional neural networks to identify them. then a GIS partial discharge recognition based on VGG-16 is proposed, which takes the GIS pattern directly as the input of the model, and extracts the feature parameter by using the convolutional layer, which avoids the subjectivity in the selection of the feature parameter. the model recognition results show that the model effectively recognizes the GIS PD types, and the accuracy of total PD recognition rate can reach 95.75%

关键词： Partial discharges Insulation Accuracy Predictive models Feature extraction Prediction algorithms Maintenance Power systems Character recognition Personnel

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AI Methods for Personalized Suggestions on Smart Glasses Based on Human Activity recognition

AI Methods for Personalized Suggestions on Smart Glasses Bas...

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4th IEEE-EMBS international conference on Wearable and Implantable Body Sensor Networks (BSN) / 18th IEEE-EMBS international conference on Biomedical and Health Informatics (BHI)

作者： Boucharas, Dimitrios G. Androutsos, Christos Tachos, Nikolaos S. Tripoliti, Evanthia E. Manousos, Dimitrios Skaramagkas, Vasileios Ktistakis, Emmanouil Marias, Kostas Tsiknakis, Manolis Fotiadis, Dimitrios I. FORTH Biomed Res Inst Ioannina Greece Univ Ioannina Dept Mat Sci & Engn Unit Med Technol & Intelligent Informat Syst Ioannina Greece FORTH Inst Comp Sci Iraklion Crete Greece Hellen Mediterranean Univ Dept Elect & Comp Engn Iraklion Crete Greece FORTH Dept Biomed Res Ioannina Greece

ISBN: (数字)9781665487917

ISBN: (纸本)9781665487917

Smart wearables are becoming an irreplaceable part of daily living by supporting their users to maintain or adopt healthier lifestyles and monitor their current status. While the trend is increasing, little has been accomplished in the field of personalized solutions. In the present study, two models derived from distinct conceptual themes were developed, and the performance was evaluated utilizing a wearable prototype in the form of smart glasses. A statistical and a reinforcement learning approach were adopted to construct a personalization layer in terms of a predefined system reaction upon specific user behavior. the settings of the present study involve the user behavior derived from Artificial Intelligence (AI) based human activity recognition, among others, and the system reaction being a supportive Augmented Reality (AR) based functionality. Each approach yielding different benefits and drawbacks, imminently leads to a comparative analysis based on the efficiency offered by assessing the inference, update, and trend handling time. Both models are built upon the user's previous data, resulting in a data driven approach that is entirely different for each user and tailored to the user preferences. the results derived from the comparative analysis indicate that both approaches offer the personalization seeked, with the reinforcement learning approach to adapt faster.

关键词： Smart glasses Sensor systems Bayes methods Q-learning

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