Weed detection and classification for autonomous farming

Kodagoda, S; Zhang, Z; Ruiz, D; Dissanayake, G

Weed detection and classification for autonomous farming

Kodagoda, S

Zhang, Z Ruiz, D Dissanayake, G

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Publisher:: I*PROMS
Publication Type:: Conference Proceeding
Citation:: Proceedings of Fourth I*PROMS Virtual International Conference, 2008, pp. 1 - 6
Issue Date:: 2008-01

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Field	Value	Language
dc.contributor.author	Kodagoda, S https://orcid.org/0000-0001-5175-9138	en_US
dc.contributor.author	Zhang, Z	en_US
dc.contributor.author	Ruiz, D	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.contributor.editor	Pham, DT	en_US
dc.contributor.editor	Eldukhri, EE	en_US
dc.contributor.editor	Soroka, AJ	en_US
dc.date	2008-07-01	en_US
dc.date.issued	2008-01	en_US
dc.identifier.citation	Proceedings of Fourth I*PROMS Virtual International Conference, 2008, pp. 1 - 6	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11108
dc.description.abstract	Autonomous weed control concepts have recently being extensively researched due to the advantages that they possess. One of the critical modules of such systems is the sensing and classification of weeds within crops. In this paper, we systematically chose the sensing setup and cues to be used for classification of two common weed species (Bidens pilosa L. and Lolium rigidum L.) in a wheat crop. An automatic cue selection followed by classification procedure is proposed. Some classification results are presented while discussing problems leading to future direction of research.	en_US
dc.publisher	I*PROMS	en_US
dc.relation.ispartof	Proceedings of Fourth I*PROMS Virtual International Conference	en_US
dc.relation.ispartof	Intelligent Production Machines and Systems	en_US
dc.title	Weed detection and classification for autonomous farming	en_US
dc.type	Conference Proceeding
utslib.location	United Kingdom	en_US
utslib.location.activity	Cardiff, UK	en_US
utslib.for	0907 Environmental Engineering	en_US
dc.location.activity	Cardiff, UK	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	open_access
pubs.consider-herdc	true	en_US
pubs.place-of-publication	United Kingdom	en_US
pubs.start-date	2008-07-01	en_US

Abstract:

Autonomous weed control concepts have recently being extensively researched due to the advantages that they possess. One of the critical modules of such systems is the sensing and classification of weeds within crops. In this paper, we systematically chose the sensing setup and cues to be used for classification of two common weed species (Bidens pilosa L. and Lolium rigidum L.) in a wheat crop. An automatic cue selection followed by classification procedure is proposed. Some classification results are presented while discussing problems leading to future direction of research.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/11108