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Computer data processing mode in the era of big data: From pattern recognition to intelligent sensing 3

Computer data processing mode in the era of big data: From p...

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3rd international conference on Intelligent Sustainable Systems, ICISS 2020

作者： Huaiyong, Deng Qing, Ma ChongQing Water Resources and Electric Engineering College Chong qing402160 China

ISBN: (纸本)9781728170893

Computer data processing mode in the era of big data from pattern recognition to intelligent sensing is discussed in this paper. Intelligence refers to the interconnection between things and things and people through the Internet of Things and mobile Internet, combined with the general big data computing, communication, artificial intelligence and other technologies. Neighborhood dependence reflects the proportion of approximate samples to all samples under decision class in mixed information system, and it is also a measure to describe the degree of relationship between conditional attribute set and decision attribute, so it can be used as a heuristic function to reduce the attribute of mixed information system. This paper designed the model from the collection to processing, from pattern analysis to the intelligent sensing. The experimental results have proven that the proposed model can sense the data effectively. © 2020 IEEE.

关键词： pattern recognition

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XXIII international conference on soft computing and Measurement, SCM 2020

XXIII International Conference on Soft Computing and Measure...

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23rd international conference on soft computing and Measurement, SCM 2020

The proceedings contain 51 papers. The topics discussed include: soft measurements of qualitative integral indicators for monitoring quantitative dataset;methodological foundations of scaling in modern measurement theory. classification of measurement scales and their application under uncertainty based on Bayesian intelligent technologies;multi-stage scale of the incentive system for distributors of an electrical company;metrological parameters of information and measurement systems for the study of a kinematic portrait of a person;combining scenario approach and choquet integral in decision making;support for the personalization of master's studies based on a fuzzy competency model (on the example of data analysis disciplines);and mutual recognition mechanism of legally significant e-documents and data in cross-border document flow.

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Deep Learning End-to-End Approach for the Prediction of Tinnitus based on EEG Data 43

Deep Learning End-to-End Approach for the Prediction of Tinn...

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43rd Annual international conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (IEEE EMBC)

作者： Allgaier, Johannes Neff, Patrick Schlee, Winfried Schoisswohl, Stefan Pryss, Ruediger Univ Wurzburg Inst Clin Epidemiol & Biometry Wurzburg Germany Univ Regensburg Dept Psychiat & Psychotherapy Regensburg Germany

ISBN: (纸本)9781728111797

Tinnitus is attributed by the perception of a sound without any physical source causing the symptom. Symptom profiles of tinnitus patients are characterized by a large heterogeneity, which is a major obstacle in developing general treatments for this chronic disorder. As tinnitus patients often report severe constraints in their daily life, the lack of general treatments constitutes such a challenge that patients crave for any kind of promising method to cope with their tinnitus, even if it is not based on evidence. Another drawback constitutes the lack of objective measurements to determine the individual symptoms of patients. Many data sources are therefore investigated to learn more about the heterogeneity of tinnitus patients in order to develop methods to measure the individual situation of patients more objectively. As research assumes that tinnitus is caused by processes in the brain, electroencephalography (EEG) data are heavily investigated by researchers. Following this, we address the question whether EEG data can be used to classify tinnitus using a deep neural network. For this purpose, we analyzed 16,780 raw EEG samples from 42 subjects (divided into tinnitus patients and control group), with a duration of one second per sample. Four different procedures (with or without noise reduction and down-sampling or up-sampling) for automated preprocessing were used and compared. Subsequently, a neural network was trained to classify whether a sample refers to a tinnitus patient or the control group. We obtain a maximum accuracy in the test set of 75.6% using noise reduction and down-sampling. Our findings highlight the potential of deep learning approaches to detect EEG patterns for tinnitus patients as they are difficult to be recognized by humans.

关键词： Deep learning soft sensors Noise reduction Electroencephalography Biology pattern recognition Biological neural networks

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A New Distance Measure Between Atanassov’s Intuitionistic Fuzzy Sets Based on Mapping 15th

A New Distance Measure Between Atanassov’s Intuitionistic F...

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15th international conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2019, co-located with the 5th international conference on Harmony Search, soft computing and Applications, ICHSA 2019

作者： Su, Fang Li, Jing Xiao, Dongxuan Duan, Chengrui School of Information and Telecommunication Engineering Beijing University of Posts and Telecommunication No. 10 Xitucheng Road Haidian District Beijing100876 China

ISBN: (纸本)9783030324551

A new trapezoidal approximation of Atanassov’s intuitionistic fuzzy sets (AIFSs) and a new distance measure between AIFSs based on the area relations of membership function graphs of their corresponding trapezoidal fuzzy sets are proposed. By the conversion from Atanassov’s intuitionistic fuzzy numbers (AIFNs) to trapezoidal fuzzy numbers, the measurement of distance between AIFSs can be transformed into the calculation of area relations of the corresponding trapezoidal fuzzy sets. Then the new distance measurement can integrate continuous information rather than only taking discrete variables into consideration as before. The main innovation of our distance is that it can integrate comprehensive and continuous information in calculation instead of partial discrete variables, which can efficiently avoid information loss. The contrastive tests demonstrate the efficiency and practicality of the approach. © Springer Nature Switzerland AG, 2020.

关键词： pattern recognition

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Center-Symmetric Local Binary pattern-Based Image Authentication Using Local and Global Features Vector 2nd

Center-Symmetric Local Binary Pattern-Based Image Authentica...

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2nd international conference on Computational Intelligence in pattern recognition (CIPR)

作者： Dey, Ashis Pal, Pabitra Chowdhuri, Partha Singh, Prabhas Kumar Jana, Biswapati Vidyasagar Univ Dept Comp Sci West Midnapore 721102 India

ISBN: (纸本)9789811524493;9789811524486

Center-symmetric local binary pattern (CS-LBP), an important tool for feature extraction, which is widely used for object recognition. In this research work, a reversible watermarking technique has been introduced for image authentication making use of local and global feature vector generated by exploiting CS-LBP, discrete cosine transform (DCT) and discrete wavelet transform (DWT). In the embedding procedure, authentication code (AC) is generated by employing CS-LBP operator on the colored cover image using a shared secret key and local feature vector and global feature vector generated by exploiting DCT and DWT which has been stored in an INFO matrix as well as embedded within the host image. In the detection procedure, authentication code (AC) is extracted with the help of a shared secret key and verified its originality by comparing it with a shared INFO matrix. Here, the symmetric property of LBP provides a minimum change in the watermarked image which helps to enhance the quality and authenticate the watermarked image.

关键词： Authentication CS-LBP Global feature Local feature Reversibility Watermark

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Realization and optimization of face recognition system based on MATLAB

Realization and optimization of face recognition system base...

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2020 international conference on Applied Physics and computing, ICAPC 2020

作者： Yan, Xi Liu, Gaqiong Department of Computer Jiangsu University of Science and Technology Zhenjiang China

In this dissertation, several techniques used in face recognition have been investigated. Besides, a critical problem in face recognition which is illumination variation has been considered. In this dissertation, a face recognition system has been built using MATLAB. In this system, after the Eigenface has been achieved, two techniques to deal with illumination changing have been implemented, shadow compensation and local binary pattern (LBP) respectively. After the experiment, LBP shows a better performance than shadow compensation on Yale B cropped database. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Local binary pattern

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Proceedings of ICPR 2020 - 25th international conference on pattern recognition

Proceedings of ICPR 2020 - 25th International Conference on ...

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25th international conference on pattern recognition, ICPR 2020

ISBN: (纸本)9781728188089

The proceedings contain 1408 papers. The topics discussed include: deep gait relative attribute using a signed quadratic contrastive loss;variational capsule encoder;the DeepHealth toolkit: a unified framework to boost biomedical applications;hierarchically aggregated residual transformation for single image super resolution;occlusion-tolerant and personalized 3D human pose estimation in RGB images;computing stable resultant-based minimal solvers by hiding a variable;semantic segmentation for pedestrian detection from motion in temporal domain;multi-label contrastive focal loss for pedestrian attribute recognition;DmifNet: 3D shape reconstruction based on dynamic multi–branch information fusion;visual localization for autonomous driving: mapping the accurate location in the city maze;Bayesian active learning for maximal information gain on model parameters;and cross-spectrum face recognition using subspace projection hashing.

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Deformed Shape Estimation of an Asymmetric Conductive pattern Printed Plate without using Resistance Model

Deformed Shape Estimation of an Asymmetric Conductive Patter...

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IEEE international conference on Real-time computing and Robotics (IEEE-RCAR)

作者： Matsuno, Takahiro Hirai, Shinichi Ritsumeikan Univ Dept Robot 1-1-1 Noji Higashi Kusatsu Shiga Japan

ISBN: (纸本)9781728172934

Thin flexible plates are widely used in various mechanisms such as springs, soft robot bodies and impulse force generators. Previous study proposed a method for estimating the deformation of thin flexible plates by printing asymmetric and symmetric electro-conductive patterns on them. However, previous method required resistance model of conductive pattern, and the method had estimation errors due to the resistance model. Therefore, in this paper, deformed shape estimation method of thin flexible plate without resistance model is proposed. In this method, constraint conditions such both edge angles and buckling distance are estimated using resistances of conductive pattern. Then, the deformation shape is estimated from constraint conditions. In this paper, this measurement flow is simulated. Simulation results showed that the better function for calculate the relationship between constraint conditions and resistances is second degree of multivariable polynomial. We find the deformed shape estimated from the resistance values of the conductive patterns are consistent with actual deformation shape in the simulation. It confirm that the deformation shape can be estimated using the proposed estimation method.

关键词： Deformation

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Comparative Analysis of Histograms of Oriented Gradients and Local Binary pattern Coefficients for Facial Emotion recognition

Comparative Analysis of Histograms of Oriented Gradients and...

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international conference on computing for Sustainable Global Development (INDIACom)

作者： Swapna Subudhiray Hemanta Kumar Palo Niva Das Sachi Nandan Mohanty ITER Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar India College of Engineering Pune Pune India

This paper examines the human expressive states dependent on facial pictures utilizing a few viable component extraction methods. It reproduces the K-Nearest Neighbor (k-NN) classifier to approve the adequacy of successful capabilities separated from the Local Binary pattern (LBP) and Histograms of Oriented Gradients (HOG) for the said task. An examination of the strategies has been made dependent on the normal acknowledgment precision of the classifiers utilizing the calculation unpredictability as a compromise. The component extraction methods have been approved for their discriminative force under various preparations for testing information division proportions, Kappa Coefficient, and order time. The LBP has outperformed the HOG include extraction strategy with a normal precision of 79.6% yet remains computationally costly. On the contrary, the HOG method has furnished a lower characterization time with a normal precision of 59.3 % as uncovered from our outcomes.

关键词： Emotion recognition Histograms Face recognition Force Feature extraction Classification algorithms Data mining

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Characteristic Analysis and pattern recognition of Arc Sound Under Typical Penetration Status in Mig Welding 4th

Characteristic Analysis and Pattern Recognition of Arc Sound...

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4th international conference on Microelectronics, computing and Communication Systems, MCCS 2019

作者： Kumari, Punam Mahto, Kartik Department of Electronics and Communication Engineering Birla Institute of Technology Mesra RanchiJharkhand835215 India

ISBN: (纸本)9789811555459

Targeting proposing a web based checking strategy for infiltration status in MIG welding, discernible bend sound sign under halfway entrance, precarious infiltration, full infiltration and extreme entrance over the span of level butt Soldering with shower move was gathered, prepared and investigated. And afterward 11 trademark constraints, which can describe weld entrance status from the points of view on schedule, recurrence, geometry-areas and cepstrum, were separated by utilizing wavelet de-noising and brief timeframe windowing. MIG butt welds of IS 2062 E250 mellow steel plates to be welded utilizing CO2 as protecting gas. Soldering speed is select as procedure variable while circular segment voltage, Soldering current, wire feed rate separation between the spout and the plates are fixed right now. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Welds

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