Generic Database for Hybrid Bayesian Pattern Recognition

A Bayesian pattern recognition system is proposed, that processes information encoded by four types of features: discrete, pseudo-discrete, multi-normal continuous and independent continuous. This hybrid system utilizes the combined frequentist-subjective approach to probabilities, uses parametric and nonparametric techniques for the conditional likelihood estimation, and relies heavily on the fuzzy theory for data presentation, learning, and information fusion. The information for training, recognition, and prediction of the system is organized in a database, which is logically structured into three interconnected hierarchical sub-databases. A software tool is created under MATLAB that assures consistency, integrity, and maintenance of the database information. Three application examples from the fields of technical and medical diagnostics are presented, which illustrate the types of problems and levels of complexity that the database tool can handle.

Download Full-text

A Video Tracking System for the Registration of Upper Extremity Motions

Успехи кибернетики / Russian Journal of Cybernetics ◽

10.51790/2712-9942-2020-1-3-3 ◽

2021 ◽

pp. 23-32

Author(s):

Ю.Г. Бурыкин

Keyword(s):

Pattern Recognition ◽

Upper Extremity ◽

Focal Length ◽

Tracking System ◽

Video Camera ◽

Recognition System ◽

Medical Diagnostics ◽

Human Motion ◽

Video Tracking ◽

Video Information

Автором рассмотрены основные способы регистрации движений верхней конечности человека с помощью различных технических средств, описаны недостатки системы видеоанализа и предложены альтернативные варианты решения ряда задач, направленных на уменьшение потери информации при видеорегистрации. Регистрация пальцевого тремора и движений пальцев осуществлялась посредством видеокамеры на основе системы распознавания образов, путем идентификации 5 меток (маркеров), сгенерированных с помощью свободной библиотеки ArUco. В результате оптимизации параметров маркеров, а также настройки углов обзора и фокусного расстояния удалось снизить ошибки при распознавании образов и повысить надежность регистрации движений фаланг пальцев с помощью видеокамеры. Использование калибровочных фотографий, полученных с экрана монитора, расположенного в различных плоскостях, позволило повысить точность регистрации движений. Информация о параметрах двигательной активности человека актуальна для объективной оценки его психофизиологического состояния и координационных способностей, а также медицинской диагностики. We considered the key methods for registering human upper extremity motions with various SW/HW tools, presented the drawbacks of video analysis systems, and proposed alternative solutions intended for reducing video information losses. We registered finger tremor/movement with a video camera and a pattern recognition system by identifying 5 markers generated with the AtUco open source library. By optimizing the marker properties, the view angles and the focal length we managed to reduce pattern recognition errors and improve phalanx movement video registration quality. Using reference photos taken from the monitor positioned at various angles also improved the motion registration quality. The human motion information is relevant to objectively assess the person’s psychophysiological status and physical coordination. It is also used for medical diagnostics.

Download Full-text

Partial Discharge Pattern Recognition of Power Transformer by Using Information Fusion

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.128-129.933 ◽

2011 ◽

Vol 128-129 ◽

pp. 933-937

Author(s):

Xin Gang Chen ◽

Yang Yang Zhao ◽

Chao Feng Zhang ◽

Xiao Xiao Tian

Keyword(s):

Pattern Recognition ◽

Information Fusion ◽

Power Transformer ◽

Partial Discharge ◽

Recognition System ◽

Experimental Models ◽

Discharge Pattern ◽

Different Types ◽

Important Sense

As one of the most important equipments in the power system, partial discharge (PD) affects the transformer’s properties in a long-term period and the partial discharge pattern recognition has most important sense. In the paper,3 kinds of experimental models simulating discharges were designed and model experiments were performed. Based on this, a transformer partial discharge pattern recognition system based on information fusion technology is developed. the finally experiments show that: information fusion have enough ability to recognize different types of partial discharge.

Download Full-text

Fuzzy Pattern Recognition of Steelmaking Process for Converter

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.97-101.4461 ◽

2010 ◽

Vol 97-101 ◽

pp. 4461-4465

Author(s):

Qi Zhao ◽

Meng Zhang ◽

Jia Li ◽

Yan Ru Chen

Keyword(s):

Pattern Recognition ◽

Light Intensity ◽

Fuzzy System ◽

Fuzzy Theory ◽

Recognition System ◽

New Method ◽

Steelmaking Process ◽

Fuzzy Pattern Recognition ◽

Fuzzy Pattern ◽

Variation Characteristics

A new method is proposed for recognizing patterns of the steelmaking process based on the light intensity from the mouth of converter. By analyzing the fuzzy theory and the measurement of variation characteristics of the light intensity, the fuzzy pattern recognition system is established. And a simulation with Matlab is then performed. The experimental results show that the fuzzy system can identify the prophase, metaphase and anaphase periods of the steelmaking effectively, and it provides a new method for the end-point auto-control of the converter steelmaking.

Download Full-text

Human Ear Pattern Recognition System

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i8.35 ◽

2017 ◽

Vol 7 (8) ◽

pp. 117 ◽

Cited By ~ 1

Author(s):

V. Jagan Naveen ◽

K. Krishna Kishore ◽

P. Rajesh Kumar

Keyword(s):

Pattern Recognition ◽

Expectation Maximization Algorithm ◽

Recognition System ◽

Modern World ◽

Person Identification ◽

Biometric Systems ◽

Different Types ◽

Recognition Systems ◽

Human Ear ◽

Pca Algorithm

In the modern world, human recognition systems play an important role to improve security by reducing chances of evasion. Human ear is used for person identification .In the Empirical study on research on human ear, 10000 images are taken to find the uniqueness of the ear. Ear based system is one of the few biometric systems which can provides stable characteristics over the age. In this paper, ear images are taken from mathematical analysis of images (AMI) ear data base and the analysis is done on ear pattern recognition based on the Expectation maximization algorithm and k means algorithm. Pattern of ears affected with different types of noises are recognized based on Principle component analysis (PCA) algorithm.

Download Full-text

Research on visual recognition intelligent system of city brand image based on fuzzy theory and regional culture

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189833 ◽

2021 ◽

pp. 1-9

Author(s):

Lin Han ◽

Lu Han

Keyword(s):

Neural Network ◽

Visual Recognition ◽

Intelligent System ◽

Brand Image ◽

Fuzzy Theory ◽

Recognition System ◽

Market Competitiveness ◽

Visual Identity ◽

Fuzzy Neural ◽

Intelligent Recognition

With the rapid development of China’s market economy, brand image is becoming more and more important for an enterprise to enhance its market competitiveness and occupy a favorable market share. However, the brand image of many established companies gradually loses with the development of society and the improvement of people’s aesthetic pursuit. This has forced it to change its corporate brand image and regain the favor of the market. Based on this, this article combines the related knowledge and concepts of fuzzy theory, from the perspective of visual identity design, explores the development of corporate brand image visual identity intelligent system, and aims to design a set of visual identity system that is different from competitors in order to shape the enterprise. Distinctive brand image and improve its market competitiveness. This article first collected a large amount of information through the literature investigation method, and made a systematic and comprehensive introduction to fuzzy theory, visual recognition technology and related theoretical concepts of brand image, which laid a sufficient theoretical foundation for the later discussion of the application of fuzzy theory in the design of brand image visual recognition intelligent system; then the fuzzy theory algorithm is described in detail, a fuzzy neural network is proposed and applied to the design of the brand image visual recognition intelligent system, and the design experiment of the intelligent recognition system is carried out; finally, through the use of the specific case of KFC brand logo, the designed intelligent recognition system was tested, and it was found that the visual recognition intelligent system had an overall accuracy rate of 96.08% for the KFC brand logo. Among them, the accuracy rate of color recognition was the highest, 96.62%; comparing the changes in the output value of the training sample and the test sample, the output convergence effect of the color network is the best; through the comparison test of the BP neural network, the recognition effect of the fuzzy neural network is better.

Download Full-text

NGSremix: A software tool for estimating pairwise relatedness between admixed individuals from next-generation sequencing data

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkab174 ◽

2021 ◽

Author(s):

Anne Krogh Nøhr ◽

Kristian Hanghøj ◽

Genis Garcia Erill ◽

Zilong Li ◽

Ida Moltke ◽

...

Keyword(s):

Next Generation Sequencing ◽

Genetic Research ◽

Likelihood Estimation ◽

Software Tool ◽

Estimation Methods ◽

Next Generation Sequencing Data ◽

Next Generation ◽

Sequencing Data ◽

Ngs Data ◽

Generation Sequencing

Abstract Estimation of relatedness between pairs of individuals is important in many genetic research areas. When estimating relatedness, it is important to account for admixture if this is present. However, the methods that can account for admixture are all based on genotype data as input, which is a problem for low-depth next-generation sequencing (NGS) data from which genotypes are called with high uncertainty. Here we present a software tool, NGSremix, for maximum likelihood estimation of relatedness between pairs of admixed individuals from low-depth NGS data, which takes the uncertainty of the genotypes into account via genotype likelihoods. Using both simulated and real NGS data for admixed individuals with an average depth of 4x or below we show that our method works well and clearly outperforms all the commonly used state-of-the-art relatedness estimation methods PLINK, KING, relateAdmix, and ngsRelate that all perform quite poorly. Hence, NGSremix is a useful new tool for estimating relatedness in admixed populations from low-depth NGS data. NGSremix is implemented in C/C ++ in a multi-threaded software and is freely available on Github https://github.com/KHanghoj/NGSremix.

Download Full-text