Feature Extraction, Feature Selection and Machine Learning for Image Classification: A Case Study

被引：0

作者：

Popescu, Madalina Cosmina ^{[1
]}

Sasu, Lucian Mircea ^{[2
,3
]}

机构：

[1] Transilvania Univ Brasov, Fac Math & Comp Sci, Brasov, Romania

[2] Transilvania Univ, Dept Math & Comp Sci, Brasov, Romania

[3] Siemens Corporate Technol RTC, Brasov, Romania

来源：

2014 INTERNATIONAL CONFERENCE ON OPTIMIZATION OF ELECTRICAL AND ELECTRONIC EQUIPMENT (OPTIM) | 2014年

关键词：

DEEP;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents feature extraction, feature selection and machine learning-based classification techniques for pollen recognition from images. The number of images is small compared both to the number of derived quantitative features and to the number of classes. The main subject is investigation of the effectiveness of 11 feature extraction/feature selection algorithms and of 12 machine learning-based classifiers. It is found that some of the specified feature extraction/selection algorithms and some of the classifiers exhibited consistent behavior for this dataset.

引用

页码：968 / 973

页数：6

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