Show simple item record

dc.contributor.authorScott, J
dc.contributor.authorBusch, A
dc.date.accessioned2021-03-24T05:39:44Z
dc.date.available2021-03-24T05:39:44Z
dc.date.issued2020
dc.identifier.isbn9781728191089en_US
dc.identifier.doi10.1109/DICTA51227.2020.9363394en_US
dc.identifier.urihttp://hdl.handle.net/10072/403386
dc.description.abstractAustralia's sugar industry is currently undergoing significant hardships, due to global market contractions from COVID-19, increased crop forecasts from larger global producers, and falling oil prices. Current planting practices utilize inefficient mass-flow planting techniques, and no attempt to map the seed using machine vision has been made, to date, in order to understand the underlying problems. This paper investigates the plausibility of creating a labeled sugarcane billet dataset using a readily-available camera positioned beneath a planter and analysing this using a YOLOv3 network. This network resulted in a high mean average precision at intersect over union of 0.5 (mAP50) of 0.852 on test images, and was used to provide planting metrics by generating a furrow map.en_US
dc.publisherIEEEen_US
dc.relation.ispartofconferencename2020 Digital Image Computing: Techniques and Applications (DICTA)en_US
dc.relation.ispartofconferencetitle2020 Digital Image Computing: Techniques and Applications, DICTA 2020en_US
dc.relation.ispartofdatefrom2020-11-29
dc.relation.ispartofdateto2020-12-02
dc.relation.ispartoflocationMelbourne, Australiaen_US
dc.relation.urihttp://purl.org/au-research/grants/ARC/IH180100002
dc.relation.grantIDIH180100002en_US
dc.relation.fundersARCen_US
dc.titleFurrow Mapping of Sugarcane Billet Density Using Deep Learning and Object Detectionen_US
dc.typeConference outputen_US
dcterms.bibliographicCitationScott, J; Busch, A, Furrow Mapping of Sugarcane Billet Density Using Deep Learning and Object Detection, 2020 Digital Image Computing: Techniques and Applications, DICTA 2020, 2020en_US
dc.date.updated2021-03-24T04:07:22Z
dc.description.versionAccepted Manuscript (AM)en_US
gro.rights.copyright© 2020 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.en_US
gro.hasfulltextFull Text
gro.griffith.authorBusch, Andrew W.
gro.griffith.authorScott, Jordan P.


Files in this item

This item appears in the following Collection(s)

  • Conference outputs
    Contains papers delivered by Griffith authors at national and international conferences.

Show simple item record