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

共 68829 条记录，以下是891-900 订阅

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Analysis of Power Loss in Coupling Mechanism for Electric Vehicle Wireless Charging System 3

Analysis of Power Loss in Coupling Mechanism for Electric Ve...

引用

2023 IEEE 3rd international conference on Data science and computer Application, ICDSCA 2023

作者： Wu, Xiaorui Gong, Wenlan Hu, Chen Mo, Yuhong Xiao, Jing Wu, Ning Electric Power Research Institute of Guangxi Power Grid Co. Ltd Southern Power Grid Corporation Wireless Power Transmission Joint Laboratory Nanning China Chongqing University College of Automation Chongqing China

ISBN: (纸本)9798350341546

Aiming at the loss analysis of the electric vehicle wireless charging system, this paper focuses on the loss of the coupling mechanism in the system, and carries out theoretical analysis and calculation from the three aspects of Litz coil loss, magnetic core loss and aluminum plate loss, and uses the COMSOL software to conduct finite element analysis to obtain the magnetic field related parameters of the coupling mechanism, and calculates the loss distribution of the coupling mechanism. Finally, combined with the loss of other links of the wireless charging system, the error between the theoretical calculation of the total loss and the actual loss measured by the electric vehicle 11KW wireless charging device is about 8%, which has a good accuracy. © 2023 IEEE.

关键词： coupling mechanism Electric vehicles loss analysis wireless charging

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Image caption generation method based on target detection 8

Image caption generation method based on target detection

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8th international conference on Intelligent Informatics and Biomedical sciences, ICIIBMS 2023

作者： Wang, Yan Wang, Ying Zhu, Jun Lou, Shuli Yantai University School of Physics and Electronic Information Yantai China Nanjing University of Information Science and Technology School of Automation Nanjing China

ISBN: (纸本)9798350369564

Image description is an important task in the field of computer vision and natural language processing, where the goal is to express the information contained in an image in captions. In this paper, we propose an image caption generation model based on the SSD target detection algorithm, which aims to improve caption accuracy. The model first extracts image features using the SSD target detection algorithm and then fuse them with features extracted from the resnet101 network to enhance the accuracy of the image information. Experimental results on the coco dataset show that this SSD target detection algorithm-based model significantly improves the accuracy of the image subtitle generation task and outperforms the traditional model in all five evaluation metrics compared to the traditional model. This research provides a useful reference for further development and practical application in the field of image caption generation. © 2023 IEEE.

关键词： Reinforcement learning

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Expression recognition based on convolutional difference contextual feature fusion

Expression recognition based on convolutional difference con...

引用

2022 international conference on Electronic Information Engineering and computer science, EIECS 2022

作者： Lu, Shengfu Yang, Chuang Li, Mi Kang, Jiaming Faculty of Information Technology Beijing University of Technology Beijing International Collaboration Base on Brain Informatics and Wisdom Services Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China Department of Automation Faculty of Information Technology Beijing University of Technology Beijing China Department of Automation Faculty of Information Technology Beijing China

ISBN: (纸本)9781510663312

Facial expression recognition has always been a focus of study in emotion computing. With the aim of solving the problem that previous facial expression recognition studies are susceptible to individual differences and background noise, as well as the loss of facial expression features in deep networks of deep convolutional networks, we propose a facial expression method based on convolutional difference contextual feature fusion. The convolutional difference module can carry out difference operation between emotional image and neutral image in the input image, eliminate individual difference and background noise in expression features and improve the accuracy and generalization of the network. Finally, convolutional difference and contextual features are combined to improve the accuracy of the network further. Experiment results of 4 public facial expression datasets illustrate that compared with the existing facial expression recognition methods, this method has higher accuracy, can extract facial expression features more effectively, and has a better generalization ability. © 2023 SPIE.

关键词： Convolutional neural networks

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Design and Assessment of a Li-Fi Based Home automation System: An Alternative to Wi-Fi and Bluetooth Communication System 2

Design and Assessment of a Li-Fi Based Home Automation Syste...

引用

2nd international conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023

作者： Imran, Mohammed Thushar Mohd Shams, Sharif Ahmed, Nayeem Refat, Rafiul Islam Rahman, Tareq Mostakim, Abdullah A.L. Brac University Dept. of Electrical Electronic Engineering Dhaka Bangladesh Brac University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350325799

This research work presents a home automation system based on Li-Fi (Light Fidelity) technology as an alternative to the RF communication systems such as Wi-Fi or Bluetooth. Li-Fi uses visible light for transmitting signals and commands through communication channels. In this literature, the usage of several types of sensors to programmatically control home appliances incorporating Li-Fi technology is thoroughly discussed. Furthermore, a prototype is constructed to assess the feasibility of the proposed system, and a Proteus based software simulation is demonstrated in parallel to corroborate the operability of the prototype. Additionally, a Tinkercad based circuit connection diagram is illustrated for better visualization of the proposed system. The study further validates that Li-Fi offers the most affordable and secure way to create a communication channel for home automation when compared to other contemporary operational devices. A technical comparison on the Li-Fi, Wi-Fi, and Bluetooth-based home automation system has also provided that emphasizes the advantages of Li-Fi over other commonly used communication technologies. Lastly, since the proposed system uses Visible Light for signal transmission, it becomes the fastest in contrast to other RF technologies now in use. © 2023 IEEE.

关键词： Bluetooth

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Phase unwrapping via deep learning for surface shape measurement by using wavelength tuning interferometry 6

Phase unwrapping via deep learning for surface shape measure...

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6th international conference on E-Business, Information Management and computer science, EBIMCS 2023

作者： Zhong, Bohang Yi, Huaian Ahn, Seokyoung Miao, Fuqing Guilin University of Technology Key Laboratory of Advanced Manufacturing and Automation Technology China Department of Mechanical Engineering Pusan National University Korea Republic of Guilin University of Technology Key Laboratory of Advanced Manufacturing and Automation Technology China

ISBN: (纸本)9798400709333

Wavelength tuning interferometry is widely used in optical metrology in order to obtain the phase information of sample. The obtained wrapped phase usually unwraps in the range of [-φ, φ]. Therefore, phase unwrapping operation is required in order to obtain the right phase. But some factors, such as phase shift miscalibration, coupling error, and noise, always lower the precision of conventional phase shifting algorithm. To address such kind of problems, we proposed a deep learning method using deep convolutional neural network to perform phase unwrapping process by turning the task into a multiclass classification work and a 2N-1 method for generating the training dataset. The results indicated that proposed method not only can compensate for phase shift miscalibration and coupling error, but also has strong robust and denoise ability, which means that proposed method is outperformed other conventional phase measurement algorithms. © 2023 ACM.

关键词： Interferometry

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Road Traffic Status Discrimination Method Based on Data Fusion of Multiple Floating Vehicles 3

Road Traffic Status Discrimination Method Based on Data Fusi...

引用

3rd international conference on Digital Signal and computer Communications, DSCC 2023

作者： Huang, Yanguo Zuo, Kefei Yang, Renzheng Jin, Chao School of electrical engineering and automation Jiangxi University of Science and Technology Ganzhou China

ISBN: (数字)9781510666566

ISBN: (纸本)9781510666559

In view of the fact that a single type of floating vehicle data can not fully reflect the traffic state of the road, this paper proposes a method to judge the urban traffic state based on multiple floating vehicle data. According to the operating characteristics of different vehicles, integrate the advantages and disadvantages of three common floating vehicles, fuse the data, and then use clustering algorithm to divide the traffic state, so as to more accurately reflect the real-time traffic state of urban roads. The experiment shows that this method has a good discrimination effect on the urban road traffic state. It can provide reference for urban road status discrimination and traffic management. © 2023 SPIE.

关键词： Data fusion

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An Attention-ReXNet Network for Long Tail Road Scene Classification 13

An Attention-ReXNet Network for Long Tail Road Scene Classif...

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13th IEEE international conference on CYBER technology in automation, Control, and Intelligent Systems, CYBER 2023

作者： Guo, Yuan H. Zhu, Jun R. Yang, Chang C. Yang, B. School of Computer Science and Artificial Intelligence Changzhou University Changzhou213000 China School of Microelectronics and Control Engineering Changzhou University Changzhou213000 China

ISBN: (纸本)9798350315196

With the development of assisted driving and autonomous driving, road scene classification has become increasingly important due to its ability to provide environmental information for drivers and autonomous driving, which is beneficial to reduce traffic accidents. However, road scene classification is limited by dataset imbalance and running speed, making it difficult to apply practically. To solve the problems mentioned above, we proposed an Attention-ReXNet network to conduct road scene classification. A balance Softmax cross-entropy is introduced to solve the class imbalance problem in road scene classification. The proposed method is evaluated in the Road Surface Classification Dataset (RSCD), which contains 27 categories and 1 million images with class imbalance. Experimental results show that Attention-ReXNet and balance Softmax cross entropy can achieve the best classification performance, with accuracy and top-1 being 87.67% and 88.52%, respectively. © 2023 IEEE.

关键词： Autonomous vehicles

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Single-board computer for Rural Traffic Counting System

Single-board Computer for Rural Traffic Counting System

引用

2023 international conference on Advanced Mechatronics, Intelligent Manufacture and Industrial automation, ICAMIMIA 2023

作者： Aliansyah, Zulhaj Yamamoto, Fuyo Jenny Farid, Imam Wahyudi Hiroshima University Infrastructure Management Laboratory Higashihiroshima Japan Jakarta Indonesia Independent Researcher Hiroshima Japan Institut Teknologi Sepuluh Nopember Electrical Automation Engineering Dept. Surabaya Indonesia

ISBN: (纸本)9798350309225

A rural traffic counting system was implemented using single-board computer paired with laser photodiodes. The system locally records the timestamp, length, and velocity of passing vehicles on a two-lane road. The system robustly worked with approximately 92% accuracy based on a one-day field test conducted in Nijo District, Masuda Municipality, Shimane Prefecture, Japan. The system offers several advantages over conventional road surface-bound vehicle detectors and traffic video surveillance pipelines, including mobile setup, absence of road obstruction, and higher possible data throughput. Furthermore, the system could be improved using data fusion with additional sensors and network connectivity between sensor nodes. The system provides an alternative for rural traffic counting, which could otherwise be unreliable, expensive, and difficult to update. © 2023 IEEE.

关键词： Roads and streets

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Grading of Academic Institutes using MCDM VIKOR Method Under Fuzzy Treatment

Grading of Academic Institutes using MCDM VIKOR Method Under...

引用

2023 international conference on New Frontiers in Communication, automation, Management and Security, ICCAMS 2023

作者： Devadas, Raghavendra M Sapna, R. Sridevi, S. Hiremani, Vani Sudha, V. Presidency University School of Computer Science and Engineering Bengaluru India University Symbiosis Institute of Technology Pune India

ISBN: (纸本)9798350317060

This paper presents a framework that combines the VIKOR technique and the fuzzy sets theory to create scientific, rational, and methodical approach for gauging academic institutions within an uncertain or fuzzy environment. In this approach, triangular fuzzy integers are used as linguistic variables to effectively manage subjectivity, uncertainty, and vagueness. Furthermore, the method tackles the complexities of multi-criteria decision-making (MCDM), where-in set of several another possibility are evaluated based on multiple criteria, offering a comprehensive solution to this challenging process. There are many MCDM methods, this paper considers on of the MCDM method known as VIKOR method, also called as (VlseKriterijumska Optimizacija I Kompromisno Resenje) in Serbian. This study takes into account four evaluation criteria viz., Faculty, Research, Alumni interaction and Faculty_Students ratio as four parameters to evaluate 5 academic institutes. The final grading of academic institutes will be based on 3 experts opinion. © 2023 IEEE.

关键词： Grading

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Machine Learning Techniques to Predict Rain Tomorrow for Automated Plant Watering System 1

Machine Learning Techniques to Predict Rain Tomorrow for Aut...

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1st international conference on Advanced Engineering and Technologies, ICONNIC 2023

作者： Asaddulloh, Bima Pramudya Aminuddin, Afrig Rahardi, Majid Abdulloh, Ferian Fauzi Yaqin, Ainul Iqbal Hasani, M. Universitas Amikom Yogyakarta Faculty of Computer Science Sleman Indonesia Universitas Teknologi Yogyakarta Faculty of Science and Technology Sleman Indonesia

ISBN: (纸本)9798350306484

This research analyzes weather classification to improve crop watering automation. Artificial intelligence algorithms such as Support Vector Machine (SVM), Naïve Bayes, and Logistic Regression are implemented to perform weather classification based on rainfall event data. A dataset of 63,677 data was used, and the K-fold cross-validation method was used to select the best model from the three algorithms based on the value of f1, accuracy, precision, and recall. The results showed that the Support Vector Machine algorithm with Linear kernel produced the highest accuracy of 71.99% at 10-fold. Naïve Bayes algorithm with the Bernoulli model produced the highest accuracy of 76.10% at 10-fold. Meanwhile, Logistic Regression produced the highest accuracy of 72.45% at a 10-fold. This research provides an overview of how artificial intelligence algorithms can be applied to classify weather in improving plant watering automation. It provides a basis for effective and accurate decision-making in plant care. © 2023 IEEE.

关键词： automation

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