Enhancing Seedling Detection in New Zealand Forestry: A Multi-Datastream Approach

dc.contributor.authorSingleton B
dc.contributor.authorXu C
dc.contributor.authorYe N
dc.contributor.authormorgenroth, justin
dc.date.accessioned2024-11-28T00:06:55Z
dc.date.available2024-11-28T00:06:55Z
dc.date.issued2024
dc.identifier.citationSingleton B, Xu C, Ye N, Morgenroth J (2024). Enhancing Seedling Detection in New Zealand Forestry: A Multi-Datastream Approach. Rotorua, New Zealand: ForestSAT. 09/09/2024-13/09/2024.
dc.identifier.urihttps://hdl.handle.net/10092/107656
dc.language.isoen
dc.rightsAll rights reserved unless otherwise stated
dc.rights.urihttp://hdl.handle.net/10092/17651
dc.subject.anzsrc30 - Agricultural, veterinary and food sciences::3007 - Forestry sciences::300709 - Tree improvement (incl. selection and breeding)
dc.subject.anzsrc30 - Agricultural, veterinary and food sciences::3007 - Forestry sciences::300707 - Forestry management and environment
dc.subject.anzsrc30 - Agricultural, veterinary and food sciences::3007 - Forestry sciences::300704 - Forest health and pathology
dc.subject.anzsrc46 - Information and computing sciences::4601 - Applied computing::460106 - Spatial data and applications
dc.subject.anzsrc46 - Information and computing sciences::4603 - Computer vision and multimedia computation::460303 - Computational imaging
dc.subject.anzsrc40 - Engineering::4007 - Control engineering, mechatronics and robotics::400703 - Autonomous vehicle systems
dc.titleEnhancing Seedling Detection in New Zealand Forestry: A Multi-Datastream Approach
dc.typeConference Contributions - Other
uc.collegeFaculty of Engineering
uc.departmentSchool of Forestry
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