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检索条件"任意字段=7th International Conference on Computing in Engineering and Technology, ICCET 2022"

共 11091 条记录，以下是991-1000 订阅

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Research on the Influence of Transverse and Axial Magnetic Field Contacts in Vacuum Interrupters on Prestrike Characteristics 7

Research on the Influence of Transverse and Axial Magnetic F...

引用

7th international conference on Electric Power Equipment - Switching technology, ICEPE-ST 2024

作者： Zhang, Zilong Chen, Pu Geng, Yun Qi, Meirong Yan, Jing Geng, Yingsan State Key Laboratory of Electrical Insulation and Power Equipment Xi'an710049 China Xi'an University of Technology Department of Electrical Engineering Xi'an710049 China

ISBN: (纸本)9798350388947

Vacuum circuit breakers (VCBs), renowned for their environmentally friendly characteristics, maintenance-free operation, excellent breaking capabilities, and prolonged mechanical and electrical lifespan, are particularly well-suited for reactive power compensation in power systems, thereby possessing significant engineering value. this paper delves into the prestrike behavior of inrush currents when switching back-to-back capacitor banks, utilizing vacuum interrupters (VIs) with two distinct contact structures: transverse magnetic field (TMF) and axial magnetic field (AMF). In the course of the experiments, both types of interrupters were exposed to various magnitudes of inrush currents multiple times, with the prestrike gap and arcing time being recorded during each closing operation. the findings reveal that, under identical conditions, the prestrike gap observed in the cup-shape TMF interrupter is narrower than that in the cup-type AMF interrupter. Nevertheless, when the magnitude of the inrush current reaches 20 kA, the cup-type AMF interrupter demonstrates superior arc extinguishing capabilities. this study serves as a stepping stone for enhancing the prestrike performance of vacuum circuit breakers in the switching of back-to-back capacitor banks in engineering applications. © 2024 IEEE.

关键词： Electric circuit breakers

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Research on Underwater Image Denoising Based on Wavelet threshold Method 7

Research on Underwater Image Denoising Based on Wavelet Thre...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Li, Chunyan Lian, Shuai Niu, Jingwei Wang, Chao Zhou, Xiaobo Research Institute Zhengzhou Electromechanical Engineering Zhoukou China

ISBN: (纸本)9781665478571

Underwater images will produce severe noise during shooting, transmission and underwater backscattering, which seriously affects the accuracy of stereo matching and target positioning. For this reason, this paper proposes an improved wavelet denoising method. First, a new continuous threshold function is designed to overcome the problem that the soft threshold will weaken the image feature information and the hard threshold is not continuous at the threshold point. After that, considering the different propagation characteristics of signal and noise at different scales of wavelet transform, an adaptive threshold estimation method that changes with the decomposition scale is proposed. Experimental results show that the improved wavelet de-noising method can not only effectively filter the noise signal, but also retain the edge information of the image to the maximum extent, making the denoised image more conducive to subsequent stereo matching and target positioning. © 2022 IEEE.

关键词： Wavelet decomposition

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NRNet: Retinex Decomposition with Realistic Noise 7

NRNet: Retinex Decomposition with Realistic Noise

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Song, Liye Yang, Jindan Li, Li Peng, Jishen Liaoning Technical University Faculty of Electrical and Control Engineering Huludao China

ISBN: (纸本)9781665478571

Computer vision tasks fail in low-light environments, so high-quality restoration of low-light images is of great significance to improve the robustness of computer vision. Traditional low-light enhancement algorithms use statistical methods or need to manually adjust parameters, which will fail in poor enhancement effect and robustness. Based on the deep learning method and the Retinex method, this paper proposes a self-supervised low-light enhancement algorithm based on the attention mechanism. We decouple the illumination component and reflection component of Retinex, and then synthesize it into an input RGB image, and finally use the estimated components to adaptively adjust different areas of the image. In experiments, we use several different datasets to test our method. Experiments show that our method is able to enhance low-light images under various scene conditions. © 2022 IEEE.

关键词： Computer vision

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Fusion of PHOG and Gabor for facial expression recognition 7

Fusion of PHOG and Gabor for facial expression recognition

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Li, Yu Ma, Hui Fang, Chunxin Lv, Wenhao Heilongjiang University School of Electronic Engineering Harbin China

ISBN: (纸本)9781665478571

Facial expression is the real expression of people's inner emotions. Research on facial expression recognition can make machines better understand human emotional information, among which feature extraction is particularly important. this paper proposes a facial expression feature extraction method based on PHOG (Pyramid Histogram of Oriented Gradients) and Gabor. PHOG can better represent the gradient information and edge direction gradient information of facial expression images. In the frequency domain, Gabor uses the multi-scale filter to extract texture features of images and filter out irrelevant face information. In this paper, we first perform principal component analysis (PCA) on the two feature operators, then fuse the two feature vectors, and finally realize facial expression recognition in static images by a support vector machine (SVM). © 2022 IEEE.

关键词： Support vector machines

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Solution method of coupling joint angle of discrete-continuous manipulator 7

Solution method of coupling joint angle of discrete-continuo...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Fang, Lijin Zhou, Zuyang Lu, Yunhua Xu, Jiqian Faculty of Robot Science and Engineering Northeastern University Shen Yang China

ISBN: (纸本)9781665478571

Recently, continuum robots capable of probing in narrow spaces have attracted a lot of attention from researchers. However, it is difficult for the current continuum robot to quickly calculate the rotation angle of each joint, so it is hard to achieve precise control of the end position. this paper design a discrete-continuous manipulator structure driven by a double tendon sheath. Based on the mechanical model of the manipulator's joint disk, establish the calculation model of the coupling angle between adjacent joints and give the relationship between the input force and the end joint angle. the method for solving the angle of each joint of the discrete-continuous manipulator is given. this model solves the problem that the angle of each joint of the discrete-continuous manipulator is hard to solve quickly, and provides a basis for the subsequent precise control of the end position of the manipulator. © 2022 IEEE.

关键词： Manipulators

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Multi-View Convolutional Neural Networks Crowd Counting Model Based on YOLOX 7

Multi-View Convolutional Neural Networks Crowd Counting Mode...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Wang, Yonghui Li, Yang Tu, Ke School of Computer Science and Engineering Shenyang Jianzhu University Shenyang China

ISBN: (纸本)9781665478571

Crowd counting refers to estimating the number of crowds and crowd distribution in images or videos, which can effectively manage pedestrian volume and observe the degree of crowd congestion in time. Single-view crowd counting has received a lot of attention in recent years and achieved remarkable performance on many public datasets. However, it is not suitable for wide-area occluded scenes due to field-of-view limitations. Multi-view crowd counting sets up multiple cameras in the same scene from multiple angles to complete crowd counting task. this paper proposes a multi-view convolutional neural networks crowd counting model based on YOLOX. Experiments are conducted on two public datasets (PETS2009, CityStreet). Results show that this method can achieve good counting accuracy and fast training speed. © 2022 IEEE.

关键词： Computer vision

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Enhanced Security Technique for Adhoc Transmission Using Hyper Elliptic Curve 7

Enhanced Security Technique for Adhoc Transmission Using Hyp...

引用

2023 7th international conference On computing, Communication, Control And Automation, ICCUBEA 2023

作者： Sudharson, K. Panimalar, S.P. Ambhika, C. Vijaya, K. Kumar, S. Pradeep Kovarasan, Rajesh Kambattan Rajalakshmi Engineering College Department of Csbs Chennai India Saveetha Engineering College Dept. of Information Technology Chennai India Velammal Institute of Technology Dept. of Information Technology Chennai India Velalar College of Engineering and Technology Department of Cse Chennai India Saveetha School of Engineering Simats Department of Cse Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Sci. and Tech. Department of Cse Chennai India

ISBN: (纸本)9798350304268

the popular cryptosystem technology with a realistic way to a highly secure and a smaller encryption bit size is known as Hyper Elliptical Curve Cryptography (HECC). the key-agreement issue is a significant drawback in the crucial demand for an explanation. A secret key must be disseminated among the clients to protect group-based data transfer in a distributed architecture. A revolutionary dynamic group secret key control is present to establish effective key distribution and administration. this article suggests key-agreement architecture based on hyperelliptic curve cryptography. the concept of the strategy, in this case, is to split a large group into multiple segments, with each segment preserving its security code to regulate the segment and managing numerous segments using a HECC management algorithm based on the Key Agreement. the study introduces a novel approach to collective key generation with encryption. An architecture for mobile networks using the Key Agreement-based HECC for Encryption (KAHECCE) suggested algorithm were simulating in contrast to the traditional techniques currently used for MANETs. KAHECCS outperforms prior methods in terms of throughput efficiency while demonstrating sophisticated key exchange characteristics without sacrificing overhead or storage costs. © 2023 IEEE.

关键词： adhoc communication cryptography elliptic curve encryption key-agreement

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Image Forgery Detection Model using CNN Architecture with SVM Classifier 7

Image Forgery Detection Model using CNN Architecture with SV...

引用

7th international conference on Parallel, Distributed and Grid computing, PDGC 2022

作者： Singh, Surjeet Sehgal, Vivek Kumar Jaypee University of Information Technology Department of Computer Science and Engineering and Infotmation Technology Waknaghat Himachal Pradesh Solan India

ISBN: (纸本)9781665454018

this Due to rapid advancement in computer vision system and easy availability of digital camera's acquisition of images and sharing the content on social media platform with falsify content is challenging task to the researcher community. For the legal purpose to provide the evidence in court, it's a difficult task identify the forgery in image that why various traditional artefacts of capturing device and internal footprints of image used to check the forgery in original image. Now a day's easy availability of software editing tools the captured image modify with wrong content to defame the person or misleading the people on social media with fake content. In this article, proposed a CNN based architecture to classify the forgery in given image. CNN architecture is capable to detect the unseen forgeries based on features extracted through various convolution layers and used SVM classifier to classify the label of forged image with high accuracy. © 2022 IEEE.

关键词： Digital forensics

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Medical Image Fusion technology Based on Low-Rank Representation of Image Blocks and Pulse Coupled Neural Network 7

Medical Image Fusion Technology Based on Low-Rank Representa...

引用

7th international conference on Image, Vision and computing, ICIVC 2022

作者： Duan, Yifan He, Kangjian Xu, Dan Yunnan University School of Information Science and Engineering Yunnan China

ISBN: (数字)9781665467346

ISBN: (纸本)9781665467346

Multimodal medical image fusion has become an indispensable part of modern medical technology. It can integrate the effective information of different modes and highlight the details. In this paper, a multimodal medical image fusion framework based on low-rank representation of image blocks and pulse coupled neural network is proposed. Firstly, the image is decomposed by NSCT. the low-frequency subband adopts the low-rank representation fusion strategy based on K-SVD dictionary learning algorithm, which strengthens the extraction of local features. the high-frequency subband adopts the pulse coupled neural network fusion. Finally, the image after NSCT inverse transform is fused with MRI gray image by guided filter to deepen the edge details. Experimental results show that the proposed fusion method has advantages over other existing algorithms in visual effect and objective metrics. © 2022 IEEE.

关键词： Image fusion

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CHS-Scheduler: A Hybrid Scheduler for QoS Task Scheduling in Cloud Human Service Scenarios 7

CHS-Scheduler: A Hybrid Scheduler for QoS Task Scheduling in...

引用

7th international conference on Cloud computing and Big Data Analytics, ICCCBDA 2022

作者： Zhang, Renyu Zhu, Zongwei University of Science and Technology of China School of Software Engineering Suzhou China

ISBN: (纸本)9781665487115

With the rapid advancement of crowdsourcing and services technology, human service ecosystem is evolving rapidly and scenarios within it are diversifying. Represented by consulting service platforms on the cloud, task scheduling in such cloud human service scenarios has more key features than traditional QoS cloud scheduling scenarios, such as dynamic human processing capability and statistical property in task flows. Rule based scheduling heuristics usually produces poor scheduling results in multi-Target scenarios and have limited adaptability as using local scheduling information. Scheduling algorithms based on meta-heuristics is time-consuming and tend to fall into local optima prematurely when facing large-scale task flows. More importantly, these scheduling methods pay little attention to optimizing those key features mentioned above. thus, an efficient task scheduling approach is urgently needed as a key to future computing systems for these scenarios. In this paper, we propose CHS-Scheduler, a hybrid scheduler for QoS task scheduling in cloud human service scenarios. Firstly, a scheduling model focusing on statistical property in task flows and dynamic human processing capability is constructed. Secondly, a two-stage scheduling methodology is given. Stage one is a task scheduling algorithm based on static & dynamic hybrid dimensionality reduction mechanism. Stage two is a solution domain mapping mechanism based on incremental learning. Experiments show that CHS-Scheduler exhibits state-of-the-Art performance in both batch scheduling and online scheduling. © 2022 IEEE.

关键词： Dimensionality reduction Crowdsourcing Cloud computing Scheduling algorithms Heuristic algorithms Ecosystems Focusing

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