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检索条件"任意字段=Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition"

共 743 条记录，以下是131-140 订阅

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MoiréVib: Micron-level Vibration Detection based on Moiré pattern 24

MoiréVib: Micron-level Vibration Detection based on Moiré ...

引用

30th international conference on Mobile computing and Networking, ACM MobiCom 2024

作者： Ning, Jingyi Yan, Zhihao Wu, Zhaowei Xie, Lei Wang, Chuyu Chen, Yingying Ye, Baoliu Lu, Sanglu State Key Laboratory for Novel Software Technology Nanjing University China Wireless Information Network Laboratory Rutgers University United States

ISBN: (纸本)9798400704895

Detection and assessment of micro vibrations are crucial tasks in both industrial settings and daily life. However, vibration sensors attached to the target vibrator may introduce potential resonance, and wireless detection methods suffer from severe multipath interference. Fortunately, moiré-based sensing methods have gained recognition in recent years due to their ability to perceive micro motion changes. In this paper, we propose MoiréVib, a micro-vibration detection solution based on moiré patterns for dynamic and high-frequency environments. We attach a printed marker with periodic gratings to the surface of vibration devices to generate moiré patterns, which can amplify micro vibrations due to their low-frequency magnification effect. However, moiré pattern's changes caused by micro vibrations are often overwhelmed by random pixel-level noises, and the limited frame rate of the camera fails to capture high-frequency moiré features. To deal with these problems, we propose a spectrum-based method to refine and enhance the dynamic and micro moiré features. Additionally, we propose a dual-frame-rate-based fusion mechanism to realize high-frequency reconstruction of moiré features. Extensive experimental results show that MoiréVib can realize a median amplitude detection error of 4.37 μm and achieve frequency detection up to 300Hz with a frame rate range of 10∼30 fps. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Vibration analysis

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Research and Application of HOG Feature Based Power Grid Key Area Out of Bounds Detection 11

Research and Application of HOG Feature Based Power Grid Key...

引用

11th international conference of Information and Communication Technology, ICTech 2022

作者： Sha, Mingrui Gu, Zhenhao Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang110168 China University of Chinese Academy of Science Beijing100049 China

ISBN: (数字)9781665496940

ISBN: (纸本)9781665496940

With the rapid development of electric power industry and the acceleration of the marketization process of electric power system reform, the importance of electric power safety production is more prominent. the traditional electronic fence mostly adopts radio frequency or infrared monitoring, which cannot be accurately identified. False positives will be generated when animals or inanimate objects enter the monitoring area. this paper aims to use interval capture method to extract feature through HOG, PCA and other feature extraction methods in real time, and then use SVM classifier to discriminate for the transgression detection system in key monitoring areas of power grid. In order to achieve the key areas of personnel crossing the precise monitoring. © 2022 IEEE.

关键词： Principal component analysis

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Implementation and Real-Time Optimization of Lwip Stack Based on AM3354 UCOS-II 11

Implementation and Real-Time Optimization of Lwip Stack Base...

引用

11th international conference of Information and Communication Technology, ICTech 2022

作者： Feng, Jinshan Wang, Pin Shenyang University of Chemical Technology Shenyang110142 China Shenyang Institute of Computing Technology Co. Ltd. Cas Shenyang110168 China

ISBN: (数字)9781665496940

ISBN: (纸本)9781665496940

According to actual needs and real-time embedded Ethernet communication, put forward a kind of by transplantation Lwip protocol stack to achieve Ethernet communication, the method of hierarchical structure clear and easy to maintain, using DMA interrupt request, realizes the Ethernet data transmission, and on this basis to optimize network communication and by adding a core layer within the Lwip priority waiting queue, the original equal data processing has been changed to give priority to processing the data in the waiting queue, and then to processing the ordinary data, so that the data processing is more flexible. the experimental test runs stably and reliably, which not only meets the security standards of the system, but also meets the requirements of embedded real-time communication. © 2022 IEEE.

关键词： Ethernet

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Industrial Control Network Security Situation Assessment Based on SAE-RBF 11

Industrial Control Network Security Situation Assessment Bas...

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11th international conference of Information and Communication Technology, ICTech 2022

作者： Li, Xinzhuang Wang, Hanjun Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang110168 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (数字)9781665496940

ISBN: (纸本)9781665496940

With the in-depth development of 'two integration', industrial control network security situation is more and more serious, industrial control network security protection work is more and more important. Aiming at the characteristics of sparse and complex dimensions of industrial control network security data, combining with the conceptual model of network security situation awareness, this paper proposes a network security situation assessment method, which uses stack self-encoder to process sparse data and uses radial basis neural network to fit complex nonlinear characteristics. It effectively extracts the data features, realizes the analysis and understanding of the data, and completes the security situation assessment, which provides a new method for the security situation assessment of the industrial control network. © 2022 IEEE.

关键词： Radial basis function networks

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A Province Time-Series Data Prognostication Model-based Unconventional Research 11

A Province Time-Series Data Prognostication Model-based Unco...

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11th international conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Sharma, Ratish Garg, Meenakshi Sanskriti University Department of Hotel Management Uttar Pradesh Mathura India Chandigarh Engineering College Department of Computer Science and Engineering Jhanjeri India

ISBN: (纸本)9781665487320

Numerous prediction issues include the extension of data or predictions because they have a temporal component. One of the most commonly used data mining techniques in business, the market, weather information, and pattern matching is series data forecasts. In order to look into the future, one must choose model that properly represent the available information. On the basis of the past, the future is projected or established. A time-order dependence is added to observations by time series. this dependence serves as a constraint as well as a foundation for more intelligence. this research presents an experimental examination of many cutting-edge time series prediction models. Data sets were analyzed, and the outcomes were assessed using the metrics MAE, MSE, RMSE, R2, and Estimated number per datapoint. © 2022 IEEE.

关键词： pattern matching

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2022 11th international conference on Modern Circuits and Systems Technologies, MOCAST 2022

2022 11th International Conference on Modern Circuits and Sy...

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11th international conference on Modern Circuits and Systems Technologies, MOCAST 2022

ISBN: (纸本)9781665467179

the proceedings contain 92 papers. the topics discussed include: a cloud computing web-based application for smart farming based on microservices architecture;a crosstalk study on metamaterial-inspired substrate integrated waveguides;a dedicated mixed-signal characterization and testing framework for novel digital security circuits that use carbon-nanotube-based physical unclonable functions;a general model for metal oxide-based memristors and application in filters;a low power low noise 65nm charge pump using mismatch compensation and smoothing capacitor;a low-latency syndrome-based deep learning decoder architecture and its FPGA implementation;a methodology for writer identification, with application to an important historical Greek document;a novel current sensing technique for photovoltaic MPPT applications;a novel piecewise chaotic map for image encryption;a silicon-proof controller system for flexible ultra-low-power energy harvesting platforms;and a study on the influence of pseudo–acceleration vector for accelerometer calibration.

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2022 IEEE 4th international conference on Power, Intelligent computing and Systems, ICPICS 2022

2022 IEEE 4th International Conference on Power, Intelligent...

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4th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2022

ISBN: (纸本)9781665467735

the proceedings contain 191 papers. the topics discussed include: virtual inertia control strategy for PV using dc capacitive and electrochemical energy storage;liquid drip detection in power plant based on machine vision;intelligent recognition algorithm of specific pattern content information based on mobile terminal equipment;research on power communication defect diagnosis technology based on unsupervised learning;key technologies of high speed modulator for satellite data transmission;research on privacy fraud detection of logistic regression based on homomorphic encryption;application research on x-ray imaging technology for online detection of gas insulated switchgear;power transformer state identification method based on operational deflection shapes and visual measurement technology;research on identification method of potential abnormal station for miniature circuit breaker;trajectory tracking error optimization based on iterative learning;research and design of the intelligent bulk transfer laboratory interconnection;energy management cloud platform in softwarized energy internet;simulation and application of a new power stealing method based on the comparison of two types of transformers;lane line detection based on machine vision;an analysis method of GIS equipment fault causes based on online monitoring and joint diagnosis;and virtual prototype design of flexible exoskeleton based on pattern recognition technology.

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Retinotopic Image Encoding by Samples of Counts 10th

Retinotopic Image Encoding by Samples of Counts

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11th international conference on pattern recognition Applications and Methods (ICPRAM)

作者： Antsiperov, Viacheslav Kershner, Vladislav RAS Kotelnikov Inst Radioengn & Elect Mokhovaya 11-7 Moscow 125009 Russia

ISBN: (纸本)9783031245374;9783031245381

the article is devoted to the synthesis of image encoding methods based on the images data themselves. the proposed approach is based on a previously developed special representation of images by samples of counts (sampling representations). Since the sampling representations are essentially random constructions, the synthesis of encoding methods is carried out strictly within the framework of the generative paradigm. In essence, the approach proposed treats the image coding within generative model as a special case of the classical statistical problem of probability distribution density estimation. In the paper we restrict ourselves to the class of parametric estimation procedures, which imply some parametric family of probability distributions. Namely, we propose to use the model of a parametric mixture of simple distribution components. Accordingly, a set of component weights estimates calculated from a sampling representation, considering as input data, is interpreted as an encoded image - output data. In this context, optimal coding is synthesized with the maximum likelihood method. For the algorithmic implementation of the coding procedure the mixture model is equipped with the structure of receptive fields, that is a well-known organizing principal for receptors in the human eye retina. On this basis, we synthesize a relatively simple recurrent coding algorithm, which turned out to be close to the popular in machine learning EM algorithm. the paper presents interpretation of several features of the algorithm from the point of view of well-known facts about the image processing in the periphery of the visual system, discusses options for the algorithm implementation, and presents the results of numerical simulation of its operation.

关键词： Perceptual image coding Generative models Machine learning

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proceedings of the 11th Euro-American conference on Telematics and Information Systems, EATIS 2022

Proceedings of the 11th Euro-American Conference on Telemati...

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11th Euro-American conference on Telematics and Information Systems, EATIS 2022

ISBN: (纸本)9781450397391

the proceedings contain 20 papers. the topics discussed include: transforming ideas and developing entrepreneurship skills in computing sciences and informatics engineering courses;low-cost clusters on big data – a systematic study;image filtering model based on convolutional neural networks for automatic counting of post-larvae in aquaculture;designing future scenarios in e-tourism;an analysis on the use of blockchain by developers and application users;a blockchain solution for crowdfunding and cost analysis;further aspects of stochastic cooperative beamforming;a systematic review on teaching parallel programming;internet of things under a semantic perspective with user profiles;and comparison of statistical methods for time synchronization between network nodes equipped with UWB transceivers.

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Swin Transformer with Multi-Scale Residual Attention for Semantic Segmentation of Remote Sensing Images 11

Swin Transformer with Multi-Scale Residual Attention for Sem...

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11th international conference on computing and pattern recognition, ICCPR 2022

作者： Lin, Yuanyang Wang, Da-Han Wu, Yun Zhu, Shunzhi Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen University of Technology Xiamen361024 China

ISBN: (纸本)9781450397056

Semantic segmentation of remote sensing images usually faces the problems of unbalanced foreground-background, large variation of object scales, and significant similarity of different classes. the FCN-based fully convolutional encoder-decoder architecture seems to have become the standard for semantic segmentation, and this architecture is also prevalent in remote sensing images. However, because of the limitations of CNN, the encoder cannot obtain global contextual information, which is extraordinarily important to the semantic segmentation of remote sensing images. By contrast, in this paper, the CNN-based encoder is replaced by Swin Transformer to obtain rich global contextual information. Besides, for the CNN-based decoder, we propose a multi-level connection module (MLCM) to fuse high-level and low-level semantic information to help feature maps obtain more semantic information and use a multi-scale upsample module (MSUM) to join the upsampling process to recover the resolution of images better to get segmentation results preferably. the experimental results on the ISPRS Vaihingen and Potsdam datasets demonstrate the effectiveness of our proposed method. © 2022 ACM.

关键词： Convolution

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