ProgramsView all programs
From the news
- Chancellor Amma Addresses the Parliament of World’s Religions
- Amrita Students Qualify for the European Mars Rover Challenge
Publication Type : Conference Paper
Publisher : IEEE
Source : In Tencon 2019-2019 IEEE Region 10 Conference (TENCON) (pp. 745–750). IEEE.
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Center for Computational Engineering and Networking (CEN), Electronics and Communication
Year : 2019
Abstract : Irrespective of the fact that Machine learning has produced groundbreaking results, it demands an enormous amount of data in order to perform so. Even though data production has been in its all-time high, almost all the data is unlabelled, hence making them unsuitable for training the algorithms. This paper proposes a novel method of extracting the features using Dynamic Mode Decomposition (DMD). The experiment is performed using data samples from Imagenet. The learning is done using SVM-linear, SVM-RBF, Random Kitchen Sink approach (RKS). The results have shown that DMD features with RKS give competing results.
Cite this Research Publication : K Rahul V, Sachin Kumar S, Neethu Mohan, KP Soman, Dynamic Mode Decomposition based feature for Image Classification, Tencon 2019, IEEE Region 10 Conference, pp 745-750, 2019. (Scopus)