Image classification using manifold learning based non-linear dimensionality reduction

This paper presents fast categorization or classification of images on an animal dataset using different classification algorithm in combination with manifold learning algorithms. The paper will focus on comparing the effects of different non-linear dimensionality reduction algorithms on speed and a...

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Bibliographic Details
Published in2018 26th Signal Processing and Communications Applications Conference (SIU) pp. 1 - 4
Main Authors Faaeq, Ainuddin, Guruler, Huseyin, Peker, Musa
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2018
Subjects
Classification algorithms
Dimensionality reduction
Forestry
Image classification
image mining
Logistics
machine learning
manifold learning
Manifolds
Support vector machines
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DOI10.1109/SIU.2018.8404441

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Summary:This paper presents fast categorization or classification of images on an animal dataset using different classification algorithm in combination with manifold learning algorithms. The paper will focus on comparing the effects of different non-linear dimensionality reduction algorithms on speed and accuracy of different classification algorithms. It examines how manifold learning algorithms can improve classification speed by reducing the number of features in the vector representation of images while keeping the classification accuracy high.
DOI:10.1109/SIU.2018.8404441