pattern recognition

Detection of primitives in images is often needed in pattern recognition and machine vision.

Cluster analysis is one of the means of multivate analysis and is widely used in pattern recognition, data mining and decision analysis etc.

Therefore, the research on pattern recognition method for the Smartongue seems to be extremely important for its improvement.

If you asked me to distill trading down to its simplest form, I would say that it is a pattern recognition numbers game.

In this work we carry out a study of pattern recognition to detect the microbiological activity in a group of heterogeneous compounds.

For geometric invariance of the invariant moment, it has been used in pattern recognition, computer vision and image reconstruction.

About the pattern recognition question very good example, may carry on the examination to the array, is extremely easy to use!

Due to its complete theoretical basis as well as excellent performance, SVM has become a hotspot in the area of pattern recognition.

Tracking individual fish in a shoal is hard. Fortunately, advances in pattern-recognition software mean it is no longer impossible.

Shape recognition of planar curves is a fundamental problem of pattern recognition. But it has not been well resolved by now.

Broderick's pattern-recognition process told him that these contrary reports were the ground truth he was looking for.

Off-line handwritten Chinese character recognition is one of the most challenging problems in pattern recognition field.

The result of experiment shows that the method excel classical operator, it establish well foundation for pattern recognition.

duda pattern classification of the ppt (Chinese version), this book sets out the classic pattern recognition methods and new methods.

Cluster analysis is an unsupervised pattern recognition frequently used in biology, where large amounts of data must often be classified.

The computer uses pattern recognition software to decide whether an image is that of a male or female.

Statistical method is widely used in pattern recognition. But it has strong specialty and is lacking for curreny.

Therefore, extraction the symmetry from complex scenes is of great significance to the pattern recognition and image processing.

The results show that this novel method is superior to pattern recognition.

Electronic Commerce, Computer Application Technology, Image Processing & Pattern Recognition, Business Intelligence.

Clustering is one of primary techniques in the filed of data mining. It is an unsupervised mode of pattern recognition.

The real threat is that the latest automated pattern-recognition software can do much of the work for less than a hundredth of it.

Uncorrelated optimal discriminant plane is an important feature extraction method and has been wildly used in the pattern recognition field.

Google recently snapped up Pittsburgh Pattern Recognition, the firm which owns the programme the researchers used for their tests.

It is one of the important methods of pattern recognition to apply neural networks to target classification.

They are wound up to a streaming video pattern recognition project.

Some of the most challenging pattern recognition problems occur when the data are in the form of pictures.

This new model does pattern recognition of control charts in quality process, to make sure that the manufacturing process is in control.

The industrial standard on weather grades for forest fire risks was presented, as well as the principle of fuzzy pattern recognition.

Handwritten character recognition is one of the research topic field of image processing and pattern recognition.

Edge plays one of important roles in the image, and the edge detection is the base of the computer vision and pattern recognition.

abstract: The innate immune system recognizes pathogen-associated molecular pattern through a series of pattern recognition receptors.

In pattern recognition and in image processing, Feature extraction is a special form of dimensionality reduction.

A method of fault pattern recognition for rolling bearings was proposed on the basis of sparse matching of a characteristic waveform (CW).

Pattern recognition criteria for biological neural signals are given and the system is applied in practical applications.

When designing your investment plan, do not bother with pattern recognition.

since more fractional orders are involved in it , anamorphic fc can be used in more complex pattern recognition.

The continued progresses of computer vision and pattern recognition technology promote the video monitoring system to be more intelligent.

Pattern recognition can be applied to identify different objects such as the human face, fingerprints, Chinese and English texts and photos.

Using the corresponding pattern recognition method, the lithologies and structures can be distinguished and identified effectively.

The feature extraction is one of the core techniques of the pattern recognition, so it is very important in the iris recognition system.

As an important module in pattern recognition, character abstraction's nature is conducting some switch to reduce dimension.

The main task of pattern recognition is dividing the samples into corresponding categories of model with the characteristics of samples.

Multiway decision tree has important applications in pattern recognition, artificial intelligence and decision support systems.

I was here in 2000 and want to share what I learned through many years of experience and historical "pattern recognition" !

The simulation shows that the algorithm can be used in the two-phase flowing pattern recognition.

The contents of Statistics, Machine Learning, Database, Pattern Recognition, Artificial Intelligence, etc are involved.

Image segmentation is an important technology in the image processing, pattern recognition and computer vision area.

In particular, how designers utilize pattern recognition, storytelling, visual communication, and empathy.

It has been widely used in the area of AI, data mining, pattern recognition, fault diagnostics, etc.

Pattern recognition is a complex process that integrates information from as many as 30 different parts of the brain.

Automatic human face recognition is attractive in pattern recognition and image procession. The human face is a complex pattern.

Cross-iteration method of fuzzy pattern recognition was applied to rationality verification of planning scheme.

Invariant moments are important measure in the pattern recognition. Invariant moments are independent of position, scale and orientation.

It was based on computerized pattern recognition, back tested on 20 years of data with breathtaking results.

At present, the main pattern recognition includes the computer pattern recognition and the optical pattern recognition.

Another set uses dedicated pattern recognition routines to detect different types of hybridisation defect in replicates.

Pattern recognition in multi-dimensional data classification is an import- ant research topic.

Pattern recognition is one of the most important areas of research and application on artificial intelligence.

We'd like to use the pattern recognition capability of the human eye to find faint, complex signals that our current algorithms miss.

With the rapid development of artificial intelligence, pattern recognition accordingly has been widely used in many fields.

Digital signal processing and pattern recognition are key research areas of this renewed effort.

Artificial mark recognition, including mark area recognition and mark pattern recognition, is a significant process of augmented reality.

BP neural network and Bayesian network are mature technology used in pattern recognition.

(pattern recognition, machine learning and intelligent monitoring).

The fault pattern recognition s of rolling bearings are thus to be effective and accurate.

Recently, as the fast development of information technology, the pattern recognition system is needed in many research areas.

With the in-depth research of computer vision technology, image processing and pattern recognition technology is widely used.

A parallel structure consisting of the decision-making level, the pattern recognition level and the feedback level is adopted.

Facial expression recognition is an active research area in pattern recognition.

A good feature extraction method helps to improve the efficiency of pattern recognition system and classification system.

It also introduces application of pattern recognition, especially image pattern recognition.

Wavelet transform is a very useful method for image features extraction and pattern recognition.

It is shown by results that the improved arithmetic for the fault diagnosis is effective and feasible in fault pattern recognition.

Feature selection is an important problem in the pattern recognition and machine learning areas.

Objective To improve traditional BP algorithm, to build effective the pattern recognition of the activity of medicament.

Fabric defect inspection using image processing technology is a problem of extracting of textural features and pattern recognition.

Learning in synergetic pattern recognition is a process by which prototype vectors and adjoint vectors are calculated.

Coclusion Chemical pattern recognition by PCA can be used to the quality evaluate. . .

The paper puts forward the idea of using fuzzy pattern recognition technique to give dynamic warning on abnormal gas-effusion.

Some of the changes in AI could also come from adaptive learning or pattern recognition.

Visual object recognition is a very active topic in computer vision and pattern recognition area.

It is said that pattern recognition have access to all areas of human life in an increasingly automated age[1-2].

With the persistent development of Digit Image Processing and Artificial Intelligence, Pattern Recognition has made great progress.

The minimum average correlation energy (MACE) filter is a well known correlation filter for pattern recognition.

This method identified flow pattern by using fast back-projection image reconstruction and fuzzy pattern recognition technique.

The application of fuzzy pattern recognition to ultrasonic detection of bonding quality of thin composite plate is studied.

It provides rich methods for pattern analysis, signal processing, syntactic pattern recognition and other pattern recognition fields.

The system realization algorithm is based on digital image processing and pattern recognition knowledge.

It is a new comprehensive monitoring of the quality of medicines using NMR combined with pattern recognition technology.

The system realization algorithm is based on digital image processing and pattern recognition knowledge.

It is a new comprehensive monitoring of the quality of medicines using NMR combined with pattern recognition technology.

The paper applies the method of language pattern recognition to identify language recognition model of isosceles triangle.

Pattern-recognition technologies are making numerous highly paid skills redundant.

Pattern recognition was conducted through one-order matching analysis in the pattern matching dictionary.

After the pretreatment and features extraction, it is preferred to use methods of pattern recognition for classification and recognition.

Probabilistic Neural Network is much more suitable to Smartongue pattern recognition than Competitive Neural Network.

Pattern recognition is not appropriate basis, but eager to get started with beginners.

Fortunately, advances in pattern-recognition software mean it is no longerimpossible.

Image processing and pattern recognition are two key technologies in the Remote Video Monitoring System Applied.

It provides for tactical threat, pattern recognition, and forensic analysis on a site-by-site or global basis.

Its application to pattern recognition is from the results obtained in classification of cracks and porosity in weld defect.

The paper refers to the theories of cell morphology, cell image segmentation and fuzzy pattern recognition.

In this thesis, we use the ATD color human vision model instead of the traditional RGB color model for polychromatic pattern recognition.

3D object recognition across multiple views is an important problem in the flied of computer vision and pattern recognition.

Signaling pathways downstream of pattern-recognition receptors and their cross talk.

This paper discussed the principles and methods of pattern recognition, and based on this, the application of pattern recognition.

Fuzzy uncertainty texture spectrum (FUTS) is applied for the pattern recognition of fracture surface morphologies.

Finally, the paper used particle swarm optimized neural network into fault pattern recognition.

MM has been widely used in the areas of image processing, machine vision and pattern recognition.

Augmented Reality uses pattern recognition to render 3D graphics on top of a video display.

A Method of Fuzzy Pattern Recognition Applied in Intelligent Traffic System for Vehicle Classification?

The PCA and the ANN are the primary pattern recognition tools in intelligent recognition.

The quality and efficiency of leucocyte test can be improved by using the digital image processing and pattern recognition.

Below we will describe four approaches to pattern recognition which arise from two different dichotomies of the starting points.

The classifier design is a key step for pattern recognition systems, which can effect performance of system.

Pattern recognition is much faster for the human mind than reading is. We read only to verify our choices.

This paper studies the quasi-pseudo-metrics of measurable classifiers in pattern recognition.

Therefore, the dual eigenspace method for automatic palmprint recognition was proposed using the subspace method of pattern recognition.

A new classify arithmetic of pattern-recognition in artificial intelligence, use support vecotr machine to classify the characteristic, C.

The technique presented in this article is a preferable one for solving the problem of pattern recognition of similarity of curves.

Pattern recognition theory is important for scientific data processing and analysis.

But the human brain is pretty good at pattern recognition too, and may sometimes beat the algorithms.

Gene selection has been widely studied in statistical pattern recognition, machine learning and data mining.

Pattern-recognition software is used to do work previously accomplished by teams of lawyers.

Introduce the principle and applications of pattern recognition.

The facility relies on the rules for pattern recognition and rules for forming the complex output message.

The pattern recognition has been an important means in seismic data interpretation and reservoir prediction.

Therefore, the neural network pattern recognition technology is also widely used and development.

In the pattern recognition strut vector machine , may use in the person face recognition training !

In the process of Optimization, we adopt the pattern recognition Mechanism to accelerate the Optimization Algorithm.

Artificial neural network pattern recognition has become especially suitable for solving a class of problem.

The K-L subspace method of pattern recognition is introduced to solve the fault diagnosis of rotating machinery.

It is a pattern recognition location technology that was tailored primarily to the metropolitan environment.

A new algorithm for reproduction pattern recognition in the cellular automata is proposed here.

You can find starting points for tracking objects in video, pattern recognition, and ideas for games.

Section for Medical Image Analysis and Pattern Recognition ENGLISH.

This thesis focuses on the application of pattern recognition to biomedical NMR study.

Pattern recognition was a field of the research on modern high-tech and it developed into an independent subject.

Multidimensional scaling is a powerful tool for dimensionality reduction in the field of pattern recognition and data mining.

Support vector machine (SVM) is a novel pattern recognition technique.

The first part deals with the proton nuclear magnetic resonance-pattern recognition research of Shengmai Capsules.

The filtering of erotic images belongs to the image pattern recognition.

The structure of fuzzy pattern recognition system, its design and implementation are emphasized with an example.

YANG Shuying. Pattern recognition and intelligent computing[M]. Beijing: Publishing House of Electronics Industry, 2008.

Currently, Manifold learning gradually becomes a hotspot in the field of machine learning and pattern recognition.

Pattern recognition software on home computers would seem a perfect tool.

It mainly consists of sensor arrays and pattern recognition systems.

This method of computing the use of powerful computer pattern recognition and the ability to 'tap' a large amount of data hidden in the law.

In this paper, we present a novel method for spectral signal pattern recognition.

Pattern representation is a basic problem of pattern recognition.

In this paper, we use fuzzy pattern recognition method to judge bonding quality.

One- class classifier is currently a hot spot of pattern recognition field.

The links below are online references for additional resources in the field of pattern recognition for machine vision.

This paper proposes a new method for detecting casing disfigurement based on image processing and pattern recognition.

This is a fingerprint recognition source code, the fingerprint recognition is the quite mature pattern recognition!

In pattern recognition, a fuzzy classifier is designed.

As the result, the research of real-time detection and automatic pattern recognition from X-ray image attracted many people.

FUZZY SHAPE PATTERN RECOGNITION METHOD?

The support vector machine (SVM) is a new pattern recognition technology based on the statistical learning theory.

Objective: To establish a system of chemical pattern recognition on the quality assessment of Bupleurum chinense DC.

In recent years, artificial neural network is widely applied in breakdown diagnosis, pattern recognition, hydrology forecast and so on.

The technology its needed include digital image processing, pattern recognition, optical character recognition and so on.

In the process of pattern recognition, we use Euclidean distance formula to classify sample.

Feature extraction is a much more difficult work in the pattern recognition but it is also a main point of the automatic tracking system.

At present, manifold learning has become a hot issue in the field of pattern recognition, machine learning and data mining.

The PC program with good man-machine interface was written by VB according to pattern recognition technology.

It's this pattern recognition process that leads to creative ideas.

A traffic pattern recognition method of elevator group control systems based on fuzzy neural networks is presented in this paper.

Based on the pattern recognition, the key parameters of affecting national income are investigated.

These models have important applications to the pattern recognition, signal processing, optimization and so on.

This paper has successfully established a content analysis system of Pro- eutectoid Ferrite Steel based on pattern recognition.

Asphalt pavement crack detection is a challenging work in the area of traffic information engineering and pattern recognition.

In pattern recognition has its unique strengths.

The second part is mainly about image processing and pattern recognition.

This paper proposes a new method of casing disfigurement detecting based on image processing and pattern recognition.

Membership function and classifier based on the fuzzy pattern recognition have been developed. 4.

Games are about pattern recognition, which is the basis for classical conditioning.

Moreover, the paper also researched how to use the algorithm in the field of the city traffic state pattern recognition problem.

A secondary simulation method based on pattern recognition and image process was proposed.

The support vector machine(SVM) is a linear classification machine, it is used commonly in the pattern recognition and nonlinear regression.

Secondly, pattern recognition for control chart is researched based on the BP neural network.

The multi-class SVM has recently been extensively applied in the field of pattern recognition.

They stick a needle in. They way we make the diagnosis today is by pattern recognition.

One-vs-rest strategy is used to solve the problem of multi-class pattern recognition.

By pattern recognition, the real-time faults are analyzed, and the results are given.

There are three different types of game you can play in Purble Place that can help teach colors, shapes, and pattern recognition.

Image-based sampling has been widely applied in many areas, including image processing, pattern recognition and so on.

It becomes a question less of scholarship and more of pattern recognition.

Besides these, R can also do a good job in pattern recognition, graphical techniques and so on, become a valuable tool for chemists.

For the study, the Carnegie Mellon team used software from Pittsburg Pattern Recognition, or PittPat.

It not only finds wide application in ITS, but also is a hot point of research in computer vision, image processing and pattern recognition.

Feature extraction is the most important step in the pattern recognition system of partial discharge.

With the development of computer graphics, pattern recognition etc, the computer vision has been developed fast.

It's pattern recognition.

Based on ORL database, the model is used to face recognition to analyze its pattern recognition capability.

You have gained in-depth knowledge of computer vision, pattern recognition and image processing.

The danger here, as Mr Campbell explains, is that we can be misled by this process of "pattern recognition" .

What is the effect of context on pattern recognition?

Image segmentation is applied in a lot of fields such as computer vision, image coding, pattern recognition, medical image and so on.

Take, for example, the notion of pattern recognition among venture capitalists.

For any kinds of pattern recognition problems, there are some values of application or reference in it.

Application of a Two-stage Fuzzy Pattern Recognition Model to the Judgment of the Main Parameters Selection in a Crane System

Fuzzy pattern recognition used for fault diagnosis of the high-pressure feed-water heater system of a 300 MW thermal power generating unit

Aim In order to study the application of fuzzy relative entropy for fuzzy pattern recognition.

object representation and recognition techniques are one of the key issues in pattern recognition and image understanding areas

Study of a Pattern Recognition Method for the On-line Dynamic Security Assessment

Energy Partition Among the Product Molecules in Microcosmic Chemical Reaction Determined by Pattern Recognition

Distortion Invariant Pattern Recognition in Terms of Synthetic Discriminant Function

Keywords: digital photogrammetry; Computer vision ; remote sensing ; registration; orthophoto update; pattern recognition

A Study of the Application of Pattern Recognition to Cantilever Structural Damage Identification

Pattern recognition applied to the fingerprint of traditional Chinese medicine characterized by two-dimension information data

Application on Imaging Pattern Recognition of A Chaotic Neural Network Simulating Olfactory Neural System

Pattern recognition of properties of alumina- magnesia castable and optimization of its technological parameters

Application of Fuzzy Pattern Recognition to the Monitoring of the Wear Condition of a Helical Cutter

The relationship of the expression of principal pattern recognition receptor with the pulmonary injury in abdominal infection-induced sepsis

The main course contents include: (I)statistical pattern recognition, (II)syntax pattern recognition, (III) fuzzy pattern recognition;

General Multi-layered Fuzzy Pattern Recognition Model and Its Application to Irrigation Technology Optimal Selection

Research and Realization of a Dynamic Multi Branches Tree Algorithm for Multi Classes Pattern Recognition

An intelligent pattern recognition algorithm and its application in cutting tool condition monitoring process

Dynamic Kernel Clustering Algorithm and Its Application in Optimal Pattern Recognition of Ethylene Production

contact component appearance; computer vision; online detection; image processing; multi-category pattern recognition;

Pattern Recognition Applied to Industrial Optimization Technology

Comparison Study of Electronic Nose Pattern Recognition Algorithms

The Conjugate Gradient Optimum Algorithm of Multi-Layers Neural Network and its Application in Pattern Recognition

Data compression and pattern recognition algorithm in a universal infrared remote control transmitter

Comparison and Study of the Algorithm of Pattern Recognition in Morphology

Study of Trace Element Table of Arthrosis Rigidity Rachitis by Computer Pattern Recognition

Application of Chemical Pattern Recognition into Classification and Quality Assessment of Chinese Traditional Medicine

Fuzzy pattern recognition model and its application tooptimizing hydroelectric installation

Simulation Study of the Neural Network Pattern Recognition of PD Failures

Study of Histological Type of Lung Cancer by Pattern Recognition and Artificial Neural Network

General Regression Neural Network Applied to the Pattern Recognition of Activity of Antagonists

Integration of rough sets and fuzzy inference system for chemical pattern recognition and its application

AIS Hypermutation Algorithm Pattern Recognition and its Application

Nerval Network Pattern Recognition Method for Condition Monitoring of Construction Machinery Hydraulic Systems

Analysis of the Relation between Instrumentation Measurement and Pattern Recognition

Basic Principle, Method of Graphic Similarity and Its Application to Structure Pattern Recognition

Dimensionality Reduction in Statistical Pattern Recognition and Low Loss Dimensionality Reduction

Application of Wavelet Analysis and Artificial Neural Network Pattern Recognition to Flaw Classification in Ultrasonic Testing

Study of pattern recognition of CCD metallography organization

Multi-layer fuzzy pattern recognition model and its application in slope stability assessment

Application of Near Infrared Reflectance Spectroscopy to the Identification of Tea Using SIMCA Pattern Recognition Method

The first two are pattern recognition problems: Finding the probability of an observed sequence given a HMM (evaluation);

Characteristics of leukocyte; cell image segmentation; Fuzzy pattern recognition; grade of membership;

Application of adaptive genetic algorithm to ultra-high-frequency partial discharge pattern recognition in transformers

A feasibility study on applying indistinct pattern recognition and modularized thinking to syndrome diagnosis of Chinese medicine

The Application of Mathematical Morphology and Pattern Recognition to Building Polygon Simplification

Application of Fuzzy Pattern Recognition to Synthetical Evaluation on Electrical Equipment Capability

Application of a Hybrid Neurosystem Based on Joint Time-Frequency Analysis for Signal Classification and Pattern Recognition