0000000001287459

AUTHOR

Ehsan Khoramshahi

0000-0002-7352-9138

showing 1 related works from this author

Tree Species Classification of Drone Hyperspectral and RGB Imagery with Deep Learning Convolutional Neural Networks

2020

Interest in drone solutions in forestry applications is growing. Using drones, datasets can be captured flexibly and at high spatial and temporal resolutions when needed. In forestry applications, fundamental tasks include the detection of individual trees, tree species classification, biomass estimation, etc. Deep neural networks (DNN) have shown superior results when comparing with conventional machine learning methods such as multi-layer perceptron (MLP) in cases of huge input data. The objective of this research is to investigate 3D convolutional neural networks (3D-CNN) to classify three major tree species in a boreal forest: pine, spruce, and birch. The proposed 3D-CNN models were emp…

010504 meteorology & atmospheric sciencesComputer sciencehyperspectral image classificationScience0211 other engineering and technologiesgeoinformatics02 engineering and technologyneuroverkot01 natural sciencesConvolutional neural networkpuulajitPARAMETERSSet (abstract data type)LIDARFORESTSClassifier (linguistics)021101 geological & geomatics engineering0105 earth and related environmental sciencesbusiness.industryDeep learningspektrikuvausQHyperspectral imagingdeep learningPattern recognition15. Life on landmiehittämättömät ilma-aluksetPerceptron113 Computer and information sciencesClass (biology)drone imagery3d convolutional neural networksmetsänarviointiMACHINEkoneoppiminentree species classification3D convolutional neural networksGeneral Earth and Planetary SciencesRGB color modelArtificial intelligencekaukokartoitusbusinesshyperspectral image classificationRemote Sensing
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