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2019 International conference on Information Technology and Computer Application, ITCA 2019

作者： Sun, Ruiyang University of Waterloo Statistics Faculty of Mathematics WaterlooONN2L 2G1 Canada

ISBN: (纸本)9781728164946

With the development of intelligent manufacturing, machine vision has become one of the indispensable technologies in many fields. The so-called machine learning is to acquire images through image sensors, analyze and process the images by computers, and then guide mechanical mechanisms to perform motion operations. As a branch of machine vision, feature matching technology is a key step of many image processing technologies. The matching degree usually directly determines the overall performance of the system. As an important component of artificial intelligence, machine learning has gradually been applied to various industries in recent years. Its intelligent characteristics make the application process achieve substantial results. This article is based on statistical classification methods, combined with the background of natural feature matching in intelligent machine learning and the main matching methods for analysis, and aims to lay the foundation for specific applications in the future. © 2019 IEEE.

关键词： Machine learning

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A Comparative Study of Data Mining, Digital image processing and Genetical Approach for Early Detection of Liver Cancer

A Comparative Study of Data Mining, Digital Image Processing...

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International conference on Computing, Power and Communication Technologies (GUCON)

作者： Meenu Sharma Rafat Parveen Jamia Millia Islamia New Delhi India

ISBN: (数字)9781728150703

ISBN: (纸本)9781728150710

Liver cancer is one of the leading causes of cancer deaths in Asia and Africa. The largest internal organ of our body is the liver. It performs many of the life sustaining functions and elementarily has effect on every physiological process occurring in our body. Liver is the second most organ which is metastatistically affected by cancer. Now a days, liver cancer becomes the main cause of death worldwide. At that time, the early prediction of liver cancer becomes necessary for increasing patient survival. In this paper, a comparison is made to know which method from genetic, data mining and digital image processing is best suited for early detection of liver cancer. After doing comparison, in this paper we decide to explore genetical approach. All the statistical methods work on microarray expression dataset and come under the category of genetical approach. Microarray data analysis evolved as an advanced research topic during recent decades. The key reason for analyzing microarray dataset is to identify and predict the gene that displays various values of expression under various testing conditions. The purpose of this research paper is to examine various forms of parametric statistical methods proposed to analyze data on microarray expression to classify the genes expressed differently and to investigate the mechanism of disease growth. Additionally, we have estimated the best situation for each system where they are doing better. In our research, we use the simulated datasets to thoroughly analyze and compare the various types of parametric methods.

关键词： statistical analysis Digital images Liver Data mining Reliability Cancer Testing

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Computer Vision Based Pre-processing for Channel Sensing in Non-stationary Environment 90

Computer Vision Based Pre-processing for Channel Sensing in ...

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90th IEEE Vehicular Technology conference (IEEE VTC-Fall)

作者： Gao, Wei Peng, Wei Liu, Jiajia Nie, Zhifeng Huazhong Univ Sci & Technol Sch Elec Info & Comm Wuhan Peoples R China HUST Shenzhen Res Inst Shenzhen Peoples R China Southeast Univ Natl Mobile Comm Res Lab Nanjing Peoples R China Northwestern Polytecn Univ Sch Cybersecur Xian Peoples R China Hubei Co Ltd China Mobile Grp Wuhan Peoples R China

ISBN: (纸本)9781728112206

With the evolution of wireless networks, new techniques including massive multiple-input multiple-output (MIMO) and millimeter wave are adopted to satisfy the demands for diversified services. However, it has been verified by field tests that the traditional wide sense stationary assumption for wireless channel does not hold anymore. As a result, traditional channel state information (CSI) acquisition methods, especially the statistical CSI acquisition, cannot be applied straightforwardly in such a circumstance. In this paper, we propose a pre-processing method for channel sensing in the non-stationary environment. Specifically, the data sampled from channel training is treated as a channel image, where the statistical channel state is represented by gray-scale. Then the computer vision technique, specifically, the edge detection method, is used on the channel image to detect the homogeneous sub-regions. Within each sub-region, the channel is statistically stationary, and then the CSI can be obtained by existing methods. It is verified by simulation results that, the proposed method can help to improve the CSI acquisition accuracy in the non-stationary environment.

关键词： Non-stationary channel CSI acquisition pre-processing computer vision

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Efficacy Of Kriging Interpolation In Ultrasound Imaging;Subsample Displacement Estimation

Efficacy Of Kriging Interpolation In Ultrasound Imaging;Subs...

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Annual International conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Brandon Rebholz Mohamed Almekkawy School of Electrical Engineering and Computer Science Penn State University PA

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Ultrasound images have an inherently low lateral resolution due to the size of transducers that are used in standard clinical scanners. This makes for low resolution images, as well as imprecise lateral displacement estimation. In speckle tracking, the well known discipline of estimating displacement by tracking pixel movement, lateral interpolation is often used to get subsample accurate displacement estimation. Standard methods for interpolation are known as inverse distance weighting methods, of which the well known cubic interpolation method is a part. Kriging interpolation, however, is a stochastic approach that uses statistical data to calculate interpolated data points as opposed to the purely mathematical methods of more traditional interpolators. This analysis tests the efficacy of one variety of Kriging interpolation, called Simple Kriging, on ultrasound data. Simple Kriging is tested on its accuracy to interpolate a sparse ultrasound image frame, as well as its usefulness in interpolating the correlation map to estimate subsample displacement. The applied bias of the estimation using Simple Kriging is also tested by interpolating the autocorrelation map where displacement is zero. Simple Kriging is an alternative interpolation scheme that could be used with image data and its accuracy is comparable to the accuracy of using the cubic interpolation.

关键词： Interpolation Estimation Correlation Ultrasonic imaging image resolution Strain Speckle

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A weighted, statistical based, No-Reference metric for holography image Quality Assessment

A weighted, statistical based, No-Reference metric for holog...

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Iranian Machine Vision and image processing (MVIP)

作者： Vahid Hajihashemi Mohammad Mehdi Arab Ameri Abdoreza Alavi Gharahbagh Hassan Pahlouvary Faculty of Engineering Kharazmi University Tehran Iran Faculty of Electrical and Computer Engineering Islamic Azad University shahrood branch Shahrood Iran Faculty of Electrical and Computer Engineering Semnan university Semnan Iran

ISBN: (数字)9781728168326

ISBN: (纸本)9781728168333

Digital holography is one of the 3D imaging systems that suffer Speckle noise. With respect to the importance of quality in 3D images, we develop an efficient general-purpose blind/no-reference holography image quality assessment metric for evaluating the quality of digital holography images. The main novelty of our approach to blind image quality assessment is based on the hypothesis that each digital holography has statistical properties that are changing in the presence of speckle noise. This change can be measured by some full reference metrics that are applied to input image and a new image, which were made by adding a known level of speckle noise to input image. These full reference measurements have the ability of identifying the distortion afflicting the input image and perform a no-reference quality assessment. In fact, adding noise to input image leads to quality loss, and the value of this loss give information about the input image quality. Finally, the result of the proposed method in estimating the quality of digital holography images were compared with some well-known full reference methods in order to demonstrate its ability.

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The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure For Least Squares 33

The Step Decay Schedule: A Near Optimal, Geometrically Decay...

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33rd conference on Neural Information processing Systems (NeurIPS)

作者： Ge, Rong Kakade, Sham M. Kidambi, Rahul Netrapalli, Praneeth Duke Univ Durham NC 27706 USA Univ Washington Seattle WA 98195 USA Cornell Univ Ithaca NY 14853 USA Microsoft Res Bengaluru India

Minimax optimal convergence rates for numerous classes of stochastic convex optimization problems are well characterized, where the majority of results utilize iterate averaged stochastic gradient descent (SGD) with polynomially decaying step sizes. In contrast, the behavior of SGD's final iterate has received much less attention despite the widespread use in practice. Motivated by this observation, this work provides a detailed study of the following question: what rate is achievable using the final iterate of SGD for the streaming least squares regression problem with and without strong convexity? First, this work shows that even if the time horizon T (i.e. the number of iterations that SGD is run for) is known in advance, the behavior of SGD's final iterate with any polynomially decaying learning rate scheme is highly sub-optimal compared to the statistical minimax rate (by a condition number factor in the strongly convex case and a factor of T in the non-strongly convex case). In contrast, this paper shows that Step Decay schedules, which cut the learning rate by a constant factor every constant number of epochs (i.e., the learning rate decays geometrically) offer significant improvements over any polynomially decaying step size schedule. In particular, the behavior of the final iterate with step decay schedules is off from the statistical minimax rate by only log factors (in the condition number for the strongly convex case, and in T in the non-strongly convex case). Finally, in stark contrast to the known horizon case, this paper shows that the anytime (i.e. the limiting) behavior of SGD's final iterate is poor (in that it queries iterates with highly sub-optimal function value infinitely often, i.e. in a limsup sense) irrespective of the stepsize scheme employed. These results demonstrate the subtlety in establishing optimal learning rate schedules (for the final iterate) for stochastic gradient procedures in fixed time horizon settings.

关键词： Gradient methods

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A study on image processing with data analysis

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AIP conference Proceedings 2022年第1期2393卷

作者： D. Chandra Prakash R. C. Narayanan N. Ganesh M. Ramachandran S. Chinnasami R. Rajeshwari 1Kgreddy College of Engineering and Technology India 2Department of Computer Science and Engineering Sona College of Technology Salem India 3Department of CSE vel tech multi tech dr. Rangarajan dr. Sakunthala Engineering College Chennai India 4REST Labs Kaveripattinam Krishnagiri India

image analysis is from images extracting meaningful information; mainly through digital image processing techniques from digital images. In this context, Tasks menu coded the tags are as simple as reading or a person from their face as sophisticated as identification. This paper presentation is made on various techniques used in analyzing images,like Computer view is from digital images or videos Dealing with how computers can gain a higher level of understanding Is an intermediate field of science, Machine vision (MV) is for applications such as automation Used to provide imaging based automation analysis and analysisTechnology and methods. Study, process control and robot guidance. Format authentication is the automatic recognition of methods and regulations in data. This includes statistical data analysis, signal processing, and Contains applications in image analysis. The dividing a digital several, the innovations are detailed in more detail in the text.

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A Combination of Deterministic Regularizations and Genetic Algorithms in Two-dimentional Inverse Scattering Problems

A Combination of Deterministic Regularizations and Genetic A...

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International conference on Telecommunications and Signal processing (TSP)

作者： Yangqing Liu Francesco Soldovieri Danilo Erricolo Department of Electrical and Computer Engineering University of Illinois at Chicago Chicago IL USA National Research Council of Italy Institute for Electromagnetic Sensing of the Environment Naples Italy

ISBN: (数字)9781728163765

ISBN: (纸本)9781728163772

The present contribution deals with a reconstruction approach to the inverse electromagnetic scattering problem based on the joint exploitation of the deterministic linear inversion and global optimization strategies. The deterministic approach is based on the Born iterative method (BIM) enhanced by regularization techniques, such as Algebraic Reconstruction Technique (ART) and Conjugate Gradient (CG). In the second step of the overall strategy, a stochastic global optimization approach, the genetic algorithm (GA), is carried out. In this way, we will benefit from the regularization schemes and address the local minima problem. Numerical results are presented with reference to the permittivity reconstructions in the case of a homogeneous cylinder and an inhomogeneous layered cylinder.

关键词： Permittivity image reconstruction Subspace constraints Inverse problems Iterative methods Genetic algorithms Scattering

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Method of Evaluation of Discrete Rhythm Structure of Cyclic Signals with the Help of Adaptive Interpolation

Method of Evaluation of Discrete Rhythm Structure of Cyclic ...

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International Computer Sciences and Information Technologies (CSIT)

作者： Iaroslav Lytvynenko Serhii Lupenko Petro Onyskiv Ternopil Ivan Puluj National Technical University Ternopil Ukraine

ISBN: (数字)9781728174433

ISBN: (纸本)9781728174440

It is presented in this paper - a new method of adaptive evaluation of a discrete rhythm structure (discrete rhythm function) of a cyclic signals based on quadratic interpolations, cubic spline, and piecewise linear interpolations. The choice of the type of interpolation function is chosen based on the information obtained through the method of determining the additional elements of the rhythm structure and the method of estimating the optimal polynomial in the segment. The developed method allows improving the accuracy of the processing of cyclic signals using methods of sampling, statistical processing and computer simulation of a wide class of cyclic signals, due to the adaptive evaluation of their discrete rhythm structure.

关键词： Rhythm Interpolation Mathematical model Splines (mathematics) Task analysis Computer simulation stochastic processes

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Vibration analysis of nylon gear box utilizing statistical method

Vibration analysis of nylon gear box utilizing statistical m...

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International conference on NanoTechnology - Ideas, Innovation and Industries

作者： Poongodi, C. Hari, B. S. Arunkumar, S. Kongu Engn Coll Dept Informat Technol Erode 638060 India Kongu Engn Coll Dept Mech Engn Erode 638060 India

Gears are important element in a variety of industrial applications such as medical and automotive sectors. In the medical field it is used in surgical instruments, Biopsy instrumentation and Dental implant products. In automotive sectors like Electrical Throttle Controls, Steering Systems, Instrument Clusters, Window and Door Latch systems. Though the plastic gears have less heat dissipation, high wear resistance and self-lubrication properties, there may be defects in nylon gears in runtime applications. The defects include surface fatigue like pitting, scuffing, scratching and some common defects like flash, warping, bubbles etc. The gear defects are often identified under switch off condition and gear are checked. There are defect testing methods like image processing. In this work the defects were identified when the system is in running condition, by analysing the vibration signals obtained from the system under varying load and speed conditions. Gears are designed based on the parameters like module, pitch circle diameter, no of teeth and bending load capacity. In this work, the experimental setup is fabricated for testing the gears at three different sets of speeds. By varying the speed of transmission between two shafts both in loading and unloading conditions, the sound signals are acquired using sound sensor and sound signals are processed using MATLAB. The timedomain signal and frequency domain signals are used to detect the failure in nylon gear. Using the parameters like kurtosis, RMS, variance and standard deviation value the good gears and defective gears are compared. By using this method the defects in nylon gears can be identified easily. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Frequency domain Kurtosis Nylon gear RMS Standard deviation Time domain Variance

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