Improving Neural Network Classification of Native Forest in New Zealand with Phenological Features​

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dc.contributor.authorYe N
dc.contributor.authormorgenroth, justin
dc.contributor.authorXu C
dc.date.accessioned2024-09-23T02:43:39Z
dc.date.available2024-09-23T02:43:39Z
dc.date.issued2024
dc.identifier.citationYe N, Morgenroth J, Xu C (2024). Improving Neural Network Classification of Native Forest in New Zealand with Phenological Features​. Rotorua, New Zealand: ForestSAT. 09/09/2024-13/09/2024.
dc.identifier.urihttps://hdl.handle.net/10092/107581
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::300707 - Forestry management and environment
dc.subject.anzsrc46 - Information and computing sciences::4601 - Applied computing::460106 - Spatial data and applications
dc.subject.anzsrc46 - Information and computing sciences::4605 - Data management and data science::460599 - Data management and data science not elsewhere classified
dc.subject.anzsrc46 - Information and computing sciences::4611 - Machine learning::461104 - Neural networks
dc.titleImproving Neural Network Classification of Native Forest in New Zealand with Phenological Features​
dc.typeConference Contributions - Other
uc.collegeFaculty of Engineering
uc.departmentSchool of Forestry
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