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Image Classification using Manifold Learning Based Non-Linear Dimensionality Reduction

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Date

2018

Author

Faaeq, Ainuddin
Gürüler, Hüseyin
Peker, Musa

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Abstract

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.

Source

2018 26Th Signal Processing and Communications Applications Conference (Siu)

URI

https://hdl.handle.net/20.500.12809/1742

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  • Bilişim Sistemleri Mühendisliği Bölümü Koleksiyonu [75]
  • Scopus İndeksli Yayınlar Koleksiyonu [6219]
  • WoS İndeksli Yayınlar Koleksiyonu [6466]



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