Pattern recognition is an innate cognitive process of matching information from the environment with the information stored in memory. Core methods are successful in many areas of numerical analysis, pattern recognition and machine learning. These are methods which generate an abstracting model from given observations (objects, measurements) in a training step, which subsequently allows generalizing statements for new observations. Various approaches are used to implement a pattern recognition system. In this paper we will discuss Statistical, Structural, hybrid and Neural Network based approach
Pattern recognition systems play a role in applications as diverse as speech recognition, optical ch...
Pattern recognition (PR) is the study of how machines can examine the environment, learn to distingu...
The paper is devoted to the description of hybrid pattern recognition method developed by research g...
Abstract – Pattern Recognition has attracted the attention of researchers in last few decades as a m...
Pattern recognition is the scientific discipline that focuses on the classification of data, objects...
Closely related to the concept of Machine Learning, Pattern Recognition is the assignment of an outp...
This tutorial article deals with the basics of artificial neural networks (ANN) and their applicatio...
The majority of current applications of neural networks are concerned with problems in pattern recog...
AbstractÐThe primary goal of pattern recognition is supervised or unsupervised classification. Among...
26 pagesFirst of all, let's give a tentative answer to the following question: what is pattern recog...
In this paper, we review some pattern recognition schemes published in recent years. After giving th...
This paper is tutorial in nature introducing the statistical and syntactic pattern recognition techn...
Pattern recognition aims to make the process of learning and detection of patterns explicit, such th...
Summary. Automatic pattern recognition is usually considered as an engineer-ing area which focusses ...
Statistical pattern recognition relates to the use of statistical techniques for analysing data meas...
Pattern recognition systems play a role in applications as diverse as speech recognition, optical ch...
Pattern recognition (PR) is the study of how machines can examine the environment, learn to distingu...
The paper is devoted to the description of hybrid pattern recognition method developed by research g...
Abstract – Pattern Recognition has attracted the attention of researchers in last few decades as a m...
Pattern recognition is the scientific discipline that focuses on the classification of data, objects...
Closely related to the concept of Machine Learning, Pattern Recognition is the assignment of an outp...
This tutorial article deals with the basics of artificial neural networks (ANN) and their applicatio...
The majority of current applications of neural networks are concerned with problems in pattern recog...
AbstractÐThe primary goal of pattern recognition is supervised or unsupervised classification. Among...
26 pagesFirst of all, let's give a tentative answer to the following question: what is pattern recog...
In this paper, we review some pattern recognition schemes published in recent years. After giving th...
This paper is tutorial in nature introducing the statistical and syntactic pattern recognition techn...
Pattern recognition aims to make the process of learning and detection of patterns explicit, such th...
Summary. Automatic pattern recognition is usually considered as an engineer-ing area which focusses ...
Statistical pattern recognition relates to the use of statistical techniques for analysing data meas...
Pattern recognition systems play a role in applications as diverse as speech recognition, optical ch...
Pattern recognition (PR) is the study of how machines can examine the environment, learn to distingu...
The paper is devoted to the description of hybrid pattern recognition method developed by research g...