A Study on Classification Techniques for Pattern Recognition

Lihong Zheng; Xiangjian He

A Study on Classification Techniques for Pattern Recognition

Research output: Book chapter/Published conference paper › Conference paper › peer-review

Abstract

In this paper, we review some pattern recognition schemes published in recent years. After giving the general processing steps of pattern recognition, we discuss several methods used for pattern recognition such as Principal Component Analysis (PCA), Support Vector Machines (SVM), Clustering and so forth. Different kinds of merits are presented and their applications on pattern precognition are given. The objective of this paper is to summarize and compare some of the methods for pattern recognition, and future research issues which need to be resolved and investigated further are given along with the new trends and ideas.

Original language	English
Title of host publication	Distributed Algorithms for Science and Engineering
Place of Publication	UK
Publisher	CMS Press
Pages	161-164
Number of pages	4
ISBN (Electronic)	1904521274
Publication status	Published - 2005
Event	Joint DCABES and ICPACE Meeting - London, UK, United Kingdom Duration: 25 Aug 2005 → 27 Aug 2005

Conference

Conference	Joint DCABES and ICPACE Meeting
Country/Territory	United Kingdom
Period	25/08/05 → 27/08/05

Cite this

@inproceedings{a05670c5de4b461eb0003db5f7e1584d,

title = "A Study on Classification Techniques for Pattern Recognition",

abstract = "In this paper, we review some pattern recognition schemes published in recent years. After giving the general processing steps of pattern recognition, we discuss several methods used for pattern recognition such as Principal Component Analysis (PCA), Support Vector Machines (SVM), Clustering and so forth. Different kinds of merits are presented and their applications on pattern precognition are given. The objective of this paper is to summarize and compare some of the methods for pattern recognition, and future research issues which need to be resolved and investigated further are given along with the new trends and ideas.",

keywords = "Feature extraction, Feature selection, Kernels, Mapping, Pattern recognition, Support vector machines",

author = "Lihong Zheng and Xiangjian He",

note = "Imported on 03 May 2017 - DigiTool details were: publisher = UK: CMS Press, 2005. editor/s (773b) = A Craig, C -H Lai; Event dates (773o) = 25-27 August 2005; Parent title (773t) = Joint DCABES and ICPACE Meeting.; Joint DCABES and ICPACE Meeting ; Conference date: 25-08-2005 Through 27-08-2005",

year = "2005",

language = "English",

pages = "161--164",

booktitle = "Distributed Algorithms for Science and Engineering",

publisher = "CMS Press",

}

TY - GEN

T1 - A Study on Classification Techniques for Pattern Recognition

AU - Zheng, Lihong

AU - He, Xiangjian

N1 - Imported on 03 May 2017 - DigiTool details were: publisher = UK: CMS Press, 2005. editor/s (773b) = A Craig, C -H Lai; Event dates (773o) = 25-27 August 2005; Parent title (773t) = Joint DCABES and ICPACE Meeting.

PY - 2005

Y1 - 2005

N2 - In this paper, we review some pattern recognition schemes published in recent years. After giving the general processing steps of pattern recognition, we discuss several methods used for pattern recognition such as Principal Component Analysis (PCA), Support Vector Machines (SVM), Clustering and so forth. Different kinds of merits are presented and their applications on pattern precognition are given. The objective of this paper is to summarize and compare some of the methods for pattern recognition, and future research issues which need to be resolved and investigated further are given along with the new trends and ideas.

AB - In this paper, we review some pattern recognition schemes published in recent years. After giving the general processing steps of pattern recognition, we discuss several methods used for pattern recognition such as Principal Component Analysis (PCA), Support Vector Machines (SVM), Clustering and so forth. Different kinds of merits are presented and their applications on pattern precognition are given. The objective of this paper is to summarize and compare some of the methods for pattern recognition, and future research issues which need to be resolved and investigated further are given along with the new trends and ideas.

KW - Feature extraction

KW - Feature selection

KW - Kernels

KW - Mapping

KW - Pattern recognition

KW - Support vector machines

M3 - Conference paper

SP - 161

EP - 164

BT - Distributed Algorithms for Science and Engineering

PB - CMS Press

CY - UK

T2 - Joint DCABES and ICPACE Meeting

Y2 - 25 August 2005 through 27 August 2005

ER -

A Study on Classification Techniques for Pattern Recognition

Abstract

Conference

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