6533b857fe1ef96bd12b466f
RESEARCH PRODUCT
Tree Species Identification Using 3D Spectral Data and 3D Convolutional Neural Network
Niko ViljanenLeevi AnnalaSamuli RahkonenEija HonkavaaraIlkka PölönenTeemu HakalaSakari TuominenOlli Nevalainensubject
medicine.medical_specialtyhahmontunnistus (tietotekniikka)010504 meteorology & atmospheric sciencesComputer scienceUAV0211 other engineering and technologiesconvolutional neural network02 engineering and technologyneuroverkot01 natural sciencesConvolutional neural networkpuulajitmedicine3D-mallinnusSpectral data021101 geological & geomatics engineering0105 earth and related environmental sciencesbusiness.industryspektrikuvausHyperspectral imagingPattern recognitionSpectral imagingRGB color modelArtificial intelligencebusinessDigital surfaceTree species3Ddescription
In this study we apply 3D convolutional neural network (CNN) for tree species identification. Study includes the three most common Finnish tree species. Study uses a relatively large high-resolution spectral data set, which contains also a digital surface model for the trees. Data has been gathered using an unmanned aerial vehicle, a framing hyperspectral imager and a regular RGB camera. Achieved classification results are promising by with overall accuracy of 96.2 % for the classification of the validation data set. nonPeerReviewed
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-09-01 |