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检索条件"任意字段=Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition"

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Transformer Anomaly recognition Method Based on Abnormal Characteristics of DGA Data 12

Transformer Anomaly Recognition Method Based on Abnormal Cha...

引用

12th international conference on the Properties and Applications of Dielectric Materials (ICPADM)

作者： Zhang, Peng Qi, Bo Yang, Pei Zhang, Ruoyu Li, Chengrong North China Elect Power Univ State Key Lab Alternate Elect Power Syst Renewabl Beijing 102206 Peoples R China Global Energy Interconnect Res Inst Co Ltd Adv Comp & Big Data Lab SGCC Beijing 102209 Peoples R China

ISBN: (纸本)9781538657881

Power transformer is one of the key electrical apparatus in power system and its reliability has directly correlation on the safety of power system. this paper presents anomaly recognition method of oil chromatographic data based on distributed computing, aiming at the existing problems that the study fails to use abnormal features of oil chromatographic data effectively to identify the abnormal and lack of the problem of identifying method for massive data anomaly. First, obtain the characteristics of abnormal data through the analysis of a large number of oil spectrum anomaly data sequence. then, Form anomaly recognition method. the method uses abnormal features of oil chromatographic data as judgment index of abnormal mode. If any abnormal pattern is met, the abnormal data can be identified. Abnormal recognition of transformer oil chromatographic data is realized on distributed computing platform. Accuracy rate of anomaly recognition is up to 89.3%. Experimental results show that this method is accurate and can be applied to distributed computing platform.

关键词： power transformer oil chromatogram data abnormal features anomaly recognition distributed computing

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A resultant of Local Binary pattern Histogram (LBPH) and Speeded up Robust Feature (SURF) algorithm for face recognition 12

A resultant of Local Binary Pattern Histogram (LBPH) and Spe...

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12th international conference on Advances in computing, Control, and Telecommunication Technologies, ACT 2021

作者： Pandey, Durgesh Kushwaha, Nitin Srivastava, Kamal Department of Computer Engineering Ambalika Institute of Management and Technology Lucknow India

In the time of increasing crime Face recognition is very significant with regards to computer vision, security, monitoring, reconnaissance, pattern checking, neural network, real-time video processing, etc. Face is non- interfering solid Biometrics for distinguishing people and subsequently goons consistently attempt to cover their faces by various fake methods, for example, plastic surgery, mask, etc. the accessibility of an exhaustive face database is vital to test the working of these algorithms of face recognition. though, we-tested freely accessible face databases as well as self-created one containing face pictures with a wide assortment of postures, light, signals and face impediments. the contribution of this research paper is Comparing Local Binary pattern Histogram (LBPH) and Speeded Up Robust Feature (SURF) algorithms and finding the best among them. © Grenze Scientific Society, 2021.

关键词： Local binary pattern

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proceedings - 20th IEEE international Symposium on Parallel and Distributed Processing with Applications, 12th IEEE international conference on Big Data and Cloud computing, 12th IEEE international conference on Sustainable computing and Communications and 15th IEEE international conference on Social computing and Networking, ISPA/BDCloud/SocialCom/SustainCom 2022

Proceedings - 20th IEEE International Symposium on Parallel ...

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20th IEEE international Symposium on Parallel and Distributed Processing with Applications, 12th IEEE international conference on Big Data and Cloud computing, 12th IEEE international conference on Sustainable computing and Communications and 15th IEEE international conference on Social computing and Networking, ISPA/BDCloud/SocialCom/SustainCom 2022

ISBN: (纸本)9781665464970

the proceedings contain 117 papers. the topics discussed include: detection of a novel dual attack in named data networking;fair DMA scheduler for low-latency accelerator offloading;multi-attribute decision-making method based on interval intuitionistic trapezoidal fuzzy number to determine the expert weight: note: sub-titles are not captured in Xplore and should not be used;binary-level directed symbolic execution through pattern learning;an efficient metric-based approach for static use-after-free detection;a graph convolution neural network based method for insider threat detection;maintenance worker scheduling for charging pile fault: a multi-agent RL approach;towards secure bilateral friend query with conjunctive policy matching in social networks;structure-noise-aware anchor link prediction across social networks;file system to support secure cloud-based sharing;discovering agent models using process mining: initial approach and a case study;and towards agent-based simulation of the parallel trading market of pharmaceuticals.

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Research on Power Voice Based on WaveNet+LSTM Improvement 12

Research on Power Voice Based on WaveNet+LSTM Improvement

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12th international conference of Information and Communication Technology, ICTech 2023

作者： Wang, HanJun Zhu, MingYun Wang, Qun University of Chinese Academy of Sciences Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350332919

With the rapid development of speech recognition [1] in recent years, the WaveNet model has also been discovered by more people and applied to speech recognition. In the open source LJSpeech-1.0, AISHELL and thch-30 and other general speech datasets, the model has achieved relatively good recognition results, but in the face of a large number of power voice data, because of the uniqueness and complexity of industry speech, the model is generally performed, so in this paper we have made some improvements to the model, aiming to improve the recognition of power-related speech data. First of all, in view of the shortcomings of the WaveNet network model in power speech recognition, we have improved and optimized it. the output gate structure of the LSTM network model is used to increase the nonlinearity of the model, so as to optimize the structural composition of the new model. We then introduced the core structure of the Reduced Convolution in WaveNet. According to the length of speech in the electric speech dataset, the receptive field of this structure is adjusted, and the sensory field is theoretically analyzed in order to better analyze the speech data. Finally, we experimentally verify the feasibility of applying the improved WaveNet model on the thch-30 dataset and the power-related dataset, and evaluate the trained model. © 2023 IEEE.

关键词： Speech recognition

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Research on Defect Segmentation Algorithm of Industrial Products Based on Transformer 12

Research on Defect Segmentation Algorithm of Industrial Prod...

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12th international conference of Information and Communication Technology, ICTech 2023

作者： Yu, Bo Yan, Zijian Wang, Wei Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Shenyang China School of Computer Sciences and Engineering Northeastern University Shenyang China

ISBN: (纸本)9798350332919

For detecting surface defects of industrial products, especially on recognition accuracy and more detailed boundary recognition, an improved semantic segmentation model based on SegFormer network is put forward in this paper. In the decoder part of the model, the bi-directional feature pyramid network (BiFPN) structure is used to receive the multi-scale feature maps output from encoder, and semantic information between feature maps of different sizes are integrated. then, the integrated semantic features are input to Boundary Refinement (BR) module to enhance Boundary information and enhance the final segmentation effect, so that the improved Segformer structure is better applicable to surface defect detection of industrial products. © 2023 IEEE.

关键词： Semantics

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Using B-spline curves for hand recognition

Using B-spline curves for hand recognition

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17th international conference on pattern recognition (ICPR)

作者： Ma, YL Pollick, F Hewitt, WT Univ Glasgow Dept Psychol Glasgow G12 8QB Lanark Scotland

ISBN: (纸本)0769521282

the B-Spline curve and surface provide an accurate tool to record object shape. We present a biometric identification system through hand geometry measurements by using B-Spline curves. We use 4 B-Spline curves to fit with fingers (except thumb) from a single hand image for a single person. then we store these 4 curves as well as other geometry measurements of the hand as the "signature" of that person into the database. By computing the differences between the curves from database hand images and the curves from the query hand image using the point projection method, we are able to verify/identify the person by locating the closest database hand image to the query hand image.

关键词： Object recognition

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n-grams of action primitives for recognizing human behavior

n-grams of action primitives for recognizing human behavior

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12th international conference on Computer Analysis of Images and patterns

作者： thurau, Christian Hlavac, Vaclav Czech Tech Univ Fac Elect Engn Dept Cybernet Ctr Machine Percept Prague 12135 2 Czech Republic

ISBN: (纸本)9783540742715

this paper presents a novel approach for behavior recognition from video data. A biologically inspired action representation is derived by applying a clustering algorithm to sequences of motion images. To obey the temporal context, we express behaviors as sequences of n-grams of basic actions. Novel video sequences are classified by comparing histograms of action n-grams to stored histograms of known behaviors. Experimental validation shows a high accuracy in behavior recognition.

关键词： Social sciences computing

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Hybrid spintronic/straintronics: A super energy efficient computing scheme based on interacting multiferroic nanomagnets

Hybrid spintronic/straintronics: A super energy efficient co...

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12th IEEE international conference on Nanotechnology (IEEE-NANO)

作者： Atulasimha, Jayasimha Bandyopadhyay, Supriyo Virginia Commonwealth Univ Dept Mech & Nucl Engn Med Coll Virginia Campus Richmond VA 23284 USA Virginia Commonwealth Univ Dept Elect & Comp Engn Med Coll Virginia Campus Richmond VA 23284 USA

ISBN: (纸本)9781467322003

We have theoretically shown that multiferroic nanomagnets (consisting of a piezoelectric and a magnetostrictive layer) could be used to perform computing while dissipating similar to few 100 kT/bit at clock rates of similar to 1GHz [1,2,3]. they can act as memory elements [2], binary logic gates [3, 4] and associative memory for four state logic [5, 6]. the latter enables signal processing functions such as ultrafast image reconstruction and pattern recognition [7]. this talk will provide an overview of our research in modeling stress induced nanoscale magnetization dynamics, its application to ultra low energy hybrid spintronic/straintronics memory and information processing, and discuss preliminary experimental work in fabrication and experimental demonstration of these devices.

关键词： straintronics spintronics multiferroic nanomagnetic logic (NML)

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Supporting Action Planning for Sedentary Behavior Change by Visualizing Personal Mobility patterns on Smartphone 18

Supporting Action Planning for Sedentary Behavior Change by ...

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12th EAI international conference on Pervasive computing Technologies for Healthcare (PervasiveHealth)

作者： Wang, Yunlong Fadhil, Ahmed Reiterer, Harald Univ Konstanz Human Comp Interact Grp Constance Germany Fdn Bruno Kessler FBK Ctr Ric GPI Trento Italy

ISBN: (纸本)9781450364508

Scientific evidence has shown that long-term sedentary behaviour is detrimental to human health. therefore, a trend appears in the field of healthy lifestyle promotion that more attention is drawn to sedentary behaviour rather than only physical activity. However, technology-based mobile health intervention tools targeting reducing sedentary behaviour are still lacking. this paper aims to explore a solution for sedentary behaviour change through supporting action planning. Action planning can not only bridge the intention-behavior gap in controlled motivation processes, but also enforce the cue-behavior association in unconscious processes. We present a smartphone-based personal mobility pattern visualization, with which we expect the users can make better action plans. the interactive visualization integrates temporal and spatial patterns of personal sedentary and walking behaviour, to provide explicit hints on when, where, and how to reduce sedentary behaviour and increase daily steps. We also present our experimental design to evaluate the visualization-based intervention tool.

关键词： Action planning sedentary behavior mobile health intervention mobility pattern visualization

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pattern recognition of Abnormal Left Ventricle Wall Motion in Cardiac MR

Pattern Recognition of Abnormal Left Ventricle Wall Motion i...

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12th international conference on Medical Image computing and Computer-Assisted Intervention (MICCAI2009)

作者： Lu, Yingli Radau, Perry Connelly, Kim Dick, Alexander Wright, Graham Sunnybrook Hlth Sci Ctr Toronto ON M4N 3M5 Canada St Micheals Hosp Cardiol Toronto ON Canada Sunnybrook Hlth Sci Ctr Cardiol Toronto ON Canada

ISBN: (纸本)9783642042706

there are four main problems that limit application of pattern recognition techniques for recognition of abnormal cardiac left ventricle (LV) wall motion: 1) Normalization of the LV's size, shape, intensity level and position;2) defining a spatial correspondence between phases and Subjects;3) extracting features;4) and discriminating abnormal from normal wall motion. Solving these four problems is required for application of pattern recognition techniques to classify the normal and abnormal LV wall motion. In this work, we introduce a normalization scheme to solve the first and second problems. With this scheme, LVs are normalized to the same position, size, and intensity level. Using the normalized images, we proposed an intra-segment classification criterion based on a con-elation measure to solve the third and fourth problems. Application of the method to recognition of abnormal cardiac MR LV wall motion showed promising results.

关键词： pattern recognition

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