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检索条件"任意字段=2023 3rd International Conference on Detection Technology and Intelligence System, DTIS 2023"

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Multi-User High-Precision Signal Simulation Method

Multi-User High-Precision Signal Simulation Method

引用

Networking systems of AI (INSAI), international conference on

作者： Rumei Chen Jianfei Xu Zhenyu Song Space Star Technology Co. Ltd. Beijing China

ISBN: (数字)9798350344660

ISBN: (纸本)9798350344677

In this paper, a high-precision multi-user signal simulation implementation method is proposed, which is mainly used for multi-user system based on DS-CDMA (Code Division Multiple Access). In the laboratory environment, multi-user signals in the actual system are simulated, which brings convenience for the debugging and testing of CDMA multi-user system, and effectively improves the efficiency of system debugging and testing.

关键词： Laboratories Debugging Hardware Multiaccess communication Artificial intelligence Satellite communications Testing

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detection of Rice Leaf Diseases to Increase its Yield by using Fuzzy Logic Approach

Detection of Rice Leaf Diseases to Increase its Yield by usi...

引用

Advancement in Electronics & Communication Engineering (AECE), international conference on

作者： Priyank Singhal Haripriya V College Of Computing Science And Information Technology Teerthanker Mahaveer University Uttar Pradesh India College of Computing Sciences And Information Technology Jain (deemed to be) University Bangalore India

The current paper describes how to set up a fuzzy expert system by using the fuzzy algorithm. A fuzzification interface, a fuzzy algorithm, and a defuzzification procedure make up a fuzzy expert system. Fuzzification methods are used in the construction of knowledge to convert exact numerical quantities into fuzzy values. The use of the fuzzy algorithm simplifies the study process for academics by facilitating the diagnosis of rice yield metrics, such as but not limited to the Number of tillers per Hill, Number of grains per panicle, and Pest and Disease incidence. A typical method is used in the given paper to perform working of fuzzy logic based on triangular approach. By using a defuzzification approach, we can transform vague or ambiguous values into precise or crisp ones. In order to create a fuzzy expert system for rice, the validation of the proposed approach is tested using MATLAB simulation.

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Study on HGR by Using Machine Learning

Study on HGR by Using Machine Learning

引用

Advance Computing and Innovative Technologies in Engineering (ICACITE), international conference on

作者： Anand Kumar Sharma A Suresh Kumar Amandeep Nagpal Rajesh Singh Dasari Veera Reddy Anupama Chadha Department of Information Technology Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering & Technology Hyderabad Department of CSE Graphic Era Deemed to be University Lovely Professional University Phagwara Uttaranchal Institute of Technology Uttaranchal University India School of Computer Science and Artificial Intelligence SR University Warangal Telangana India Department of Computer Applications Manav Rachna International Institute of Research and Studies Faridabad Haryana

The medical field and other research areas fields heavily rely on artificial intelligence (AI) and machine learning (ML). Hand gesture recognition (HGR), which is a straightforward approach for interacting with machines, has drawn the attention of numerous researchers in the context of AI. Utilizing ML technique, HGR is carried out. Both the image technique and the design approach are parts of it. In the image technique, the hand picture is rebuilt utilizing the attributes of the images. However, when using the model-based approach, the image is recreated using many models, including volumetric, geometric, and others. The key difficulty in gesture control continues to be the ML individual's complexity and preparation time. Its accuracy is used to assess the HGR accuracy. Its precision is used to assess the HGR overall system performance. The many techniques and algorithms utilized in gesture control are covered in detail inside this work.

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Vehicle Theft detection Using Neural Pattern Recognition

Vehicle Theft Detection Using Neural Pattern Recognition

引用

Pervasive Computing and Social Networking (ICPCSN), international conference on

作者： J. Jane Rubel Angelina S.J Subhashini Anil Kumar Rapuri Vennela Ravva Raghavendra Rasala Sai Dcepak Ray Adurgam Dept of Computer Science and Engineering Kalasalingam Academy Of Research And Education Krishnankoil TamilNadu India Dept of Computer Science and Engineering SRM Madurai College for Engineering and Technology Sivagangai TamilNadu India

Finding stolen cars is becoming increasingly important in many urban regions. An automated system for scanning license plates can recognize vehicle numbers without the need for human interaction. This work proposes a vehicle theft detection system based on neural pattern recognition, gaussian filter, and equilibrium optimization. The proposed architecture has significant speedup and higher accuracy rates. The proposed number plate recognition method has a maximum accuracy rate of 94% and an average reduction in the processing time of 32%. Pattern recognition is the process of detecting regularities and patterns in data using machine learning. These analogies may now be uncovered via statistical analysis, historical data, or machine-generated knowledge.

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YOLOv4-tiny Mask detection Algorithm Based on Attention Mechanism

YOLOv4-tiny Mask Detection Algorithm Based on Attention Mech...

引用

Electronic technology, Communication and Information (ICETCI), IEEE international conference on

作者： Tao Liu Wenju Song School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China

Properly wearing a mask can help prevent many respiratory infections, such as COVID-19. The mask detection system reminds people in public places to wear masks. Therefore, it is necessary to develop an efficient mask detection algorithm. This paper proposes a YOLOv4-tiny mask detection algorithm with an attention mechanism for complex and changeable situations and small-scale target detection. The algorithm comprises the following steps. First, a hybrid domain attention mechanism CBAM is added to the feature map output by the backbone network as the input of the feature fusion network so that the network pays more attention to the effective area of the sample during training. Second, the Mosaic data enhancement method enriches the data so the model can learn global and local features better. Moreover, the learning rate cosine annealing attenuation strategy is used in training to accelerate the convergence of the model. In this paper, 5983 images are selected from WIDER Face and MAFA data sets to form a face mask data set for training and testing of the algorithm. The experimental results show that the map of the model can reach 85.21 %, the model parameters are small, and the detection speed can reach 87.79 FPS. Therefore, it is convenient for people to deploy it on mobile devices and realize real-time detection.

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Research on sentiment analysis of weibo based on Improving Capsule Network

Research on sentiment analysis of weibo based on Improving C...

引用

Consumer Electronics and Computer Engineering (ICCECE), 2021 IEEE international conference on

作者： Hui Shao Computer Engineering Technology College (Artificial Intelligence College) Guangdong Polytechnic of Science and Technology Zhuhai China

When conducting text sentiment analysis based on traditional deep learning models, lack of extracting deep-seated characteristics and sentence system characteristics etc. The article propose a model based on improving capsule networks. This model uses Weibo text as the research object, and uses BERT to obtain the word vector; then use CNN to extract deep phrase characteristics, LSTM networks to model the dependencies of each word in the instance, and dig out its hidden semantics; then increase attention layer is screened with effective features; finally, the improved capsule network is used to express a richer expression of text sentiment information to enhance the overall abstraction capabilities of the model. After experimenting on the dataset, it achieved good results on Weibo's sentiment analysis. The result shows that the model is better than traditional models, and it also fully shows that the model can effectively improve the accuracy of sentiment analysis.

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Ship Intrusion detection technology Based on Bayesian Optimization Algorithm and XGBoost

Ship Intrusion Detection Technology Based on Bayesian Optimi...

引用

Electrical Engineering and Control Science (IC2ECS), international conference on

作者： Aobo Zhou Qi Zhu Jundong Zhang Ke Meng School of Marine Engineering Dalian Maritime University Dalian Liaoning China

Cybersecurity is a prerequisite for maritime safety. This study focuses on intelligent ship integrated automation system, analyzing the principles and shortcomings of these system. We propose a machine learning-based intrusion detection solution that utilizes Recursive Feature Elimination (RFE) as a feature selection algorithm and XGBoost as a classification algorithm. The Bayesian optimization algorithm is applied to optimize the hyperparameters of the XGBoost model for detecting anomalous network data. Results indicate that, compared to decision trees, logistic regression, random forests, KNN, and recent research findings, the proposed method exhibits smaller estimation errors with an overall accuracy of 99.8%. It effectively reduces vulnerabilities in ship networks, achieving a F1-score of 96.37% and a recall rate of 96.33% under sufficient dataset conditions. This approach enhances network security performance and elevates the cybersecurity level of intelligent ships.

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Analysis of Machine Learning for Recognizing Hand Gestures

Analysis of Machine Learning for Recognizing Hand Gestures

引用

Advance Computing and Innovative Technologies in Engineering (ICACITE), international conference on

作者： Anand Kumar Sharma A Suresh Kumar Amandeep Nagpal Rajesh Singh DasariVeera Reddy Anupama Chadha Department of Information Technology Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering & Technology Hyderabad Department of CSE Graphic Era Deemed to be University Lovely Professional University Phagwara Uttaranchal Institute of Technology Uttaranchal University India School of Computer Science and Artificial Intelligence SR University Warangal Telangana India Department of Computer Applications ManavRachna International Institute of Research and Studies Faridabad Haryana

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A Modified Three-Phase Synchronous Isothermal Relaxation Current detection system Based on Independent Measurement Loop Method

A Modified Three-Phase Synchronous Isothermal Relaxation Cur...

引用

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

作者： Hai Li Bangle He Bin Shen Jiawei Chen Yunjie Zhou Tianyu Yang Xinyang Zhu Yalin Wang State Grid Shanghai Cable Company Shanghai China Shanghai Jiao Tong University Shanghai China

As a nondestructive testing technique, the isothermal relaxation current (IRC) method has been applied to assess the condition of power cable insulation. In order to shorten the detection time in the field and improve the measurement accuracy, a modified measurement circuit based on an independent measurement loop was proposed to discharge the interference from the high-voltage insulated wires. Based on this circuit, the three-phase synchronous IRC measurement system was established. Furthermore, the independence and consistency of the three-phase current measurement loop were verified, which could realize the synchronous acquisition of the three-phase relaxation current. Finally, the three-phase IRC test was carried out to evaluate the aging state of the sample in service. The results showed that the aging state of each phase for the same cable might be quite different after long service.

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Design of General Intelligent Control Platform for Thermal Power Plants

Design of General Intelligent Control Platform for Thermal P...

引用

Intelligent Power and systems (ICIPS), international conference on

作者： Zhaojin Chen Wenjing Zhang Changgeng Wang Chunyu Gao Dongsheng Wei Weiting Zhen Hongyi Guo Yanhong Cui Chunyu Zhang Meng Liang Junfeng Long Yuan Fang Inner Mongolia Datang International Tuoketuo Power Generation Co. Ltd. Huhehaote China China Datang Corporation Science and Technology Research Institute North China Electric Power Test and Research Institute Beijing China

Intelligent control system (ICS) is a new type of control system that combines advanced intelligent control technologies, such as big data and artificial intelligence, with traditional DCS, and it is the development direction of realizing production process intelligence in thermal power plants. In this paper, for the third-party intelligent applications other than DCS manufacturers, and in view of the deficiencies of existing intelligent control systems in terms of integration and extensibility, we propose a general intelligent control platform architecture design based on "microservices + containerization" and "unified interface + modularization". The platform integrates DCS internal communication interface and human-computer interaction interface, realizes the integrated monitoring and closed-loop control of general intelligent control platform and DCS, and is compatible with a variety of DCS and intelligent applications developed in different programming languages. The successful on-line operation of the general intelligent control platform on a 600MW unit of a power plant has verified the rationality and effectiveness of the system architecture design.

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