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检索条件"任意字段=Proceedings of the 3rd International Conference on Control and Computer Vision"

共 18814 条记录，以下是931-940 订阅

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An Enhanced Repetitive control Framework for Adaptive Neuro-Fuzzy Learning Grid-Connected Inverter with Current control and Frequency Adaptability 3

An Enhanced Repetitive Control Framework for Adaptive Neuro-...

引用

3rd international conference on Trends in Electrical, Electronics and computer Engineering, TEECCON 2024

作者： Reddy, SiripiReddy Venkateswarlu Hemakesavulu, O. Basha, Ch. Hussaian Irfan, M. Mujahid Sarika, Daruru Peera, Dudekula Gouse Annamacharya University Department of Eee Andhra Pradesh Rajampet India Annamacharya University Department of Eee Andhra Pradesh Rajampet India Sr University Department of Eee Telangana Warangal India Annamacharya University Department of Cse Andhra Pradesh Rajampet India Annamacharya University Department of Civil Andhra Pradesh Rajampet India

ISBN: (纸本)9798331505714

This work proposes an advanced repeated control method (RCM) for a frequency adaptable grid-connected inverter based on fuzzy current control. The primary goal of the suggested strategy is to lower total harmonic distortion (THD) by adjusting the FIR filter in accordance with shifting grid frequencies while maintaining resonant frequencies that match both the fundamental and harmonic grid frequencies. When it is necessary that the sampling frequency ratio be an integer, the repeated control system is chosen due to its high efficiency in tracking periodic signals and low output total harmonic distortion (THD). The RCM's resonant frequencies will deviate from the actual grid's fundamental and harmonic frequencies in an industrial setting where the ratio may not be an integer. As a result, the system's performance may be negatively impacted. against determine whether the suggested control method improves performance, it is compared against a conventional repeated control strategy that uses a PI controller. Through trials conducted at various frequencies, the control approach is assessed in grid-connected mode. The suggested controller successfully demonstrates its superiority over alternative control schemes with regard to the inverter systems' THD level and component harmonic. © 2024 IEEE.

关键词： FIR filters

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A novel relative entropy based FCM algorithm using interval type-2 fuzzy set at local membership functions for brain MR image segmentation 3

A novel relative entropy based FCM algorithm using interval ...

引用

3rd IEEE international conference on control, Instrumentation, Energy and Communication, CIEC 2024

作者： Ray, Madhumita Sing, Jamuna Kanta Jadavpur University Computer Science and Engineering Department Kolkata India

ISBN: (纸本)9798350313703

In this proposed article, we develop a fuzzy c-means algorithm based on relative entropy for segmentation of noisy volumetric brain MR images and introduce interval type-2 fuzzy membership functions by using local membership functions as a secondary membership function. The brain magnetic resonance images are influenced by high level of intensity inhomogeneity (IIH) and noise, because of the limitations of machinery devices and cognitive limitations of the operators. As a result it produces blurry images, mostly at the soft tissue boundary regions. This phenomenon increases uncertainty for the image soft tissue classification. The proposed algorithm handle this issue by incorporating interval type-2 fuzzy (IT2F) set at the local membership functions to reduce the underlying uncertainty factors of each voxels more efficiently. It also integrates the total uncertainties for volumetric images by utilizing relative entropy. At first, the proposed algorithm generates the global and local membership functions for each voxel, next, it generates type-2 fuzzy (T2F) set by considering local membership functions as a secondary membership functions and finally, the algorithm generates IT2F set by doing direct defuzzificaton of the T2F set. We conduct qualitative and quantitative experiments on ten different simulated volumes of brain MR images. The results revel the outcome of the experiments and it indicates the supremacy of the proposed algorithm over the state-of-the-art algorithms established in near past. © 2024 IEEE.

关键词： Fuzzy clustering

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UAV Swarm control Algorithm Based on Kalman Filter and Particle Swarm Optimization 3

UAV Swarm Control Algorithm Based on Kalman Filter and Parti...

引用

3rd international conference on Applied Mathematics, Modelling, and Intelligent Computing, CAMMIC 2023

作者： Qiu, Hongyi Yan, Tingting Ma, Long Yue, Guodong School of Mechanical Engineering Shenyang Jianzhu University Shenyang110168 China School of Science Shenyang Jianzhu University Shenyang110168 China

ISBN: (数字)9781510667617

ISBN: (纸本)9781510667600

This paper studies the passive localization and control of two-dimensional planar UAV swarm under velocity information and azimuth information. We propose a UAV swarm control algorithm based on azimuth information and velocity information. This paper establishes a positioning model through azimuth information. On this basis, the IMU information is fused for attitude calculation. Moreover, the inertial navigation positioning is established by using the attitude angle and velocity information, so as to explore and use the optimal estimation theory. Through Kalman filter technology, the Gaussian noise interference in UAV positioning is greatly eliminated, and the positioning algorithm of UAV swarm is established. In addition, using the azimuth information, the particle swarm optimization is used for path planning, and the target path planning results with higher accuracy are obtained. Through computer simulation analysis, the algorithm has the characteristics of high positioning accuracy and fast iteration speed. The algorithm can better meet the practical engineering application requirements. © 2023 SPIE.

关键词： Unmanned aerial vehicles (UAV)

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Target detection method based on improved YOLOv3 3

Target detection method based on improved YOLOv3

引用

3rd international conference on computer vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Jia, YiXin Liu, LuYang Zhang, LiJie Li, Hai Changchun University of Technology Department of Software Engineering Jilin Province Changchun China Changchun University of Technology Department of Computer Science and Technology Jilin Province Changchun China Changchun University of Technology School of Computer Science and Engineering Jilin Province Changchun China Jilin University Computer Technology Jilin Province Changchun China

ISBN: (纸本)9781665459112

With the continuous development of the field of computer vision and the need for the accuracy and timeliness of model recognition in practical applications, YOLOv3 draws on YOLOvl and YOLOv2. Although there are not many innovations, it maintains the speed advantage of the YOLO family and the detection accuracy is improved, especially for the detection ability of small objects [1]. However, in the three-layer feature network structure of YOLOv3, the correlation between the layers is not strong, which may lead to the situation that the information of the input image cannot be used efficiently, thus affecting the final accuracy. In this regard, this paper mainly studies the improvement method for the YOLOv3 feature pyramid network, and there are many improvement methods for this network. This paper uses residual linking and attention mechanism methods. The fusion judgment of features is realized by introducing the CBAM attention module and adding residual links in the same layer and residual links across layers. Finally, we use the VOC07+12 dataset [2] to obtain an accuracy of 79.5% under the condition of IoU=0.75 after 150 iterations, which is an improvement compared to the 73.6% accuracy of the original model. © 2022 IEEE.

关键词： Object detection

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Design of service robot control system for epidemic prevention and control 3

Design of service robot control system for epidemic preventi...

引用

3rd IEEE international conference on Power, Electronics and computer Applications, ICPECA 2023

作者： Zhang, Xinjing Chen, Yingxi Ma, Weiwei Xi'An University of Science and Technology Xi'an China Sichuan Agricultural University Ya'an China China Three Gorges University Yichang China

ISBN: (纸本)9781665472784

In view of the fact that Covid-19 is highly contagious, which poses great threat and inconvenience to people's production and life, a multifunctional robot control system with single-chip microcomputer as the control core is designed, aiming at the problems of centralized isolation points in communities, complicated situation and difficult management. Firstly, Gmapping algorithm is used to realize the robot's autonomous positioning and avoidance. Secondly, a three-degree-of-freedom robot arm is designed to disinfect any indoor space. Finally, Gmapping algorithm is used to recognize and measure the temperature of human face. Through the simulation experiment, this method can improve the efficiency of searching the shortest path and carry out disinfection work while reducing human contact, improving public safety and has practical value. © 2023 IEEE.

关键词： Mobile robots

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Research on the Innovation System of computer Artificial Intelligence Technology in Museum Financial Management System 3

Research on the Innovation System of Computer Artificial Int...

引用

3rd IEEE international conference on Power, Electronics and computer Applications, ICPECA 2023

作者： Wang, Siyu Yunnan University Yunnan Kunming China

ISBN: (纸本)9781665472784

This paper designs a museum financial management system based on computer artificial intelligence technology. The system introduces RPA technology to automatically collect, identify and classify image data of image recognition, speech recognition and original documents to help improve the efficiency of voucher entry and audit. This paper focuses on the general ledger management certificate of museum financial sharing service center to optimize the design of financial process automation. The system realizes the concentration and integration of business and financial activities through the process reengineering of financial fund settlement, accounting, budget preparation and financial analysis of the museum, so as to improve the quality of financial information disclosure, budget management and internal control efficiency of the museum. © 2023 IEEE.

关键词： Image enhancement

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Research on bridge surface defects based on YOLOv7 3

Research on bridge surface defects based on YOLOv7

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3rd international conference on Electronic Information Engineering, Big Data, and computer Technology, EIBDCT 2024

作者： Jiang, Qinghe Zhang, Hui Zhang, Hongyan Jiang, Wenping Shenyang Jianzhu University School of Electrical and Control Engineering Shenyang China

ISBN: (纸本)9781510680449

This paper explores deep learning methods for bridge surface defect detection, particularly an improved model based on YOLOv7. To address the detection of bridge-type defects, a Dual-Stream Attention Module (DSAM) and a Hybrid Atrous Pyramid Module (DP) were introduced, aiming to enhance the model's capability to capture key features and the efficiency of multi-scale feature extraction. Experimental results show that the improved model demonstrates higher detection accuracy on a bridge defect dataset, with the YOLOv7+DSAM+DP model achieving a mean Average Precision (mAP) of 91.3%. Additionally, the study compares the SSD and Faster R-CNN networks, confirming the superiority of the proposed model. Overall, the model presented in this paper significantly improves the precision and efficiency of bridge surface defect detection by integrating attention mechanisms and hybrid atrous pyramid modules. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Efficiency

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Brightness gain and maximum output brightness adjustment method and test system of third-generation Low-light-level image intensifier 3

Brightness gain and maximum output brightness adjustment met...

引用

3rd international Computing Imaging conference, CITA 2023

作者： Ren, Yingnan Yan, Bo Zhang, Linlin Jiao, Gangcheng Ni, Xiaobing Song, Haihao Science and Technology on Low-Light-Level Night Vision Laboratory Xi’an710065 China Kunming Institute of Physics Kunming650223 China

ISBN: (纸本)9781510671409

For the current brightness gain and maximum output brightness adjustment method of image intensifier has low efficiency, time-consuming, low precision, and other problems, this paper firstly studies a communication protocol from the perspective of digital communication of auto-gating power supply microcontroller. By means of communication with the host computer, the corresponding parameters of the internal program of the auto-gating power supply microcontroller are adjusted. Secondly, the hardware interface of the whole tube communication of the image intensifier is designed. Finally, the calibrated experimental device is used to adjust the brightness gain and maximum brightness of the whole tube, and the automatic brightness control function of the adjusted whole tube is verified. The adjustment time is short, the adjustment precision is high, and the matching between the auto-gating power supply and the image tube can be better realized. © 2023 SPIE.

关键词： Luminance

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Floor Water Detection Technology Based on Improved Resnet 3

Floor Water Detection Technology Based on Improved Resnet

引用

3rd IEEE international conference on computer Communication and Artificial Intelligence, CCAI 2023

作者： Hao, Ruijie Xia, Siyi Fang, Youbin Yan, Taiyu College of Artificial Intelligence Nankai University Tianjin China College of Computer Science Nankai University Tianjin China

ISBN: (纸本)9798350335262

With the rapid development of artificial intelligence and the arrival of an aging population, the need for intelligent service robots is increasing. Older adults and the blind are susceptible to slipping due to weak vision, especially when they cannot see water on indoor floors. We use computer vision technology to solve this problem. However, it is challenging to detect floor water using existing target detection algorithms due to uncertainty about its shape and size. This paper proposes a floor water detection technology based on improved Resnet, which can be deployed on the intelligent service robot to remind the elderly and the blind to be careful When the service robot detects water in the ground. Our proposed topics and methods can significantly reduce the probability of the elderly and blind people slipping. The method proposed in this paper is 3.6% higher than the original Resnet18 and 8.1% higher than Mobilenetv2;the number of parameters in our method is only 8.5 percent of VGG16_bn and yet achieves similar performance to VGG16_bn. This paper suggests a new trajectory for intelligent service robots by detecting water on the floor, and it has demonstrated promising results in accuracy and speed. It is hoped that this paper will arouse more scholars' interest in the detection technology of floor water. © 2023 IEEE.

关键词： Floors

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A study of algorithms for generating descriptions of emotionally stylized images with labels 3

A study of algorithms for generating descriptions of emotion...

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3rd international conference on Optics and Machine vision, ICOMV 2024

作者： Wang, S. Huanxin Zheng, R. Gengsheng School of Computer Science and Engineering Wuhan Institute of Technology No. 206 Optics Valley 1st Road East Lake High-tech Development Zone Jiangxia District Wuhan430205 China

ISBN: (纸本)9781510680319

Generating stylized captions for images is a challenging task, in order to solve this problem, this paper proposes a new stylized image captioning method M-tag. we design a memory module M containing a set of embedding vectors for encoding stylistically relevant phrases in a training corpus. To obtain style-related phrases, we develop a sentence decomposition algorithm P, which divides the stylized sentence into a style-related part that reflects the linguistic style and a content-related part that contains the visual content. Transformer encoder is used to encode the target of target features within the image and swin-Transformer encoder is used to encode the relational features within the image to jointly encode different aspects of information within the image from different perspectives. The stylized target features encoded by the target Transformer are fused with the relational features encoded by the swin-Transformer through the splicing method to achieve the purpose of fusion of intra-image relational features and local target *** generating the caption, the content-related style knowledge is first extracted from the memory module through the noticing mechanism, and the extracted style features are then integrated into the language model, and finally the fused encoded features are decoded to generate the corresponding image description using the Transformer decoder. © 2024 SPIE.

关键词： Signal encoding

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