Automated Plant Identification using Artificial Neural Networks

Clark, JY, Corney, DPA and Tang, HL (2012) Automated Plant Identification using Artificial Neural Networks In: CIBCB'12, 2012-05-09 - 2012-05-12, San Diego, USA.

Preview	Text CIBCB2012_final_as_submitted18Mar2012.pdf Available under License : See the attached licence file. Download (244kB)
Preview	Text (licence) SRI_deposit_agreement.pdf Download (33kB)

Abstract

This paper describes a method of training an artificial neural network, specifically a multilayer perceptron (MLP), to act as a tool to help identify plants using morphological characters collected automatically from images of botanical herbarium specimens. A methodology is presented here to provide a practical way for taxonomists to use neural networks as automated identification tools, by collating results from a collection of neural networks. A case study is provided using data extracted from specimens of the genus Tilia in the Herbarium of the Royal Botanic Gardens, Kew, UK.

Item Type:	Conference or Workshop Item (Conference Paper)
Divisions :	Faculty of Engineering and Physical Sciences > Computer Science
Authors :	Clark, JY, Corney, DPA and Tang, HL
Date :	14 June 2012
DOI :	10.1109/CIBCB.2012.6217250
Contributors :	Contribution Name Email ORCID http://www.loc.gov/loc.terms/relators/PBL IEEE,
Additional Information :	© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User :	Symplectic Elements
Date Deposited :	23 Sep 2013 15:42
Last Modified :	06 Jul 2019 05:13
URI:	http://epubs.surrey.ac.uk/id/eprint/803211

Actions (login required)

View Item

Downloads