Deakin University
Browse

File(s) under permanent embargo

Transfer learning using the online FMM model

chapter
posted on 2014-01-01, 00:00 authored by M Seera, Chee Peng LimChee Peng Lim, C K Loo
In this paper, we present an analysis on transfer learning using the Fuzzy Min-Max (FMM) neural network with an online learning strategy. Transfer learning leverages information from the source domain in solving problems in the target domain. Using the online FMM model, the data samples are trained one at a time. In order to evaluate the online FMM model, a transfer learning data set, based on data samples collected from real landmines, is used. The experimental results of FMM are analyzed and compared with those from other methods in the literature. The outcomes indicate that the online FMM model is effective for undertaking transfer learning tasks.

History

Title of book

Neural information processing : 21st International Conference ICONIP 2014 Kuching, Malaysia, November 3-6, 2014 Proceedings, Part I

Volume

8834

Series

Lecture Notes in Computer Science

Chapter number

19

Pagination

151 - 158

Publisher

Springer

Place of publication

Berlin, Germany

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783319126364

Language

eng

Publication classification

B Book chapter; B1 Book chapter

Extent

77

Editor/Contributor(s)

C Loo, K Yap, K Wong, A Teoh