Related publication(s) of the modelling presented in the Jupyter notebook
Cross-site learning in deep learning rgb tree crown detection
Deepforest: a python package for rgb deep learning tree crown delineation
Individual tree-crown detection in rgb imagery using semi-supervised deep learning neural networks
Contains input NeonTreeEvaluation RGB images used in the Jupyter notebook of Tree crown detection using DeepForest
Contains outputs, (figures), generated in the Jupyter notebook of Tree crown detection using DeepForest
Rendered version of the Jupyter Notebook hosted by the Environmental Data Science Book
Online rendered version of the Jupyter notebook
Lock conda file for osx-64 OS of the Jupyter notebook hosted by the Environmental Data Science Book
Lock conda file for win-64 OS of the Jupyter notebook hosted by the Environmental Data Science Book
Pip requirements file containing libraries to install after conda lock
Pip requirements for lock conda environments
Conda environment when user want to have the same libraries installed without concerns of package versions
Jupyter Notebook hosted by the Environmental Data Science Book
The research object refers to the Tree crown detection using DeepForest notebook published in the Environmental Data Science book.
Tree crown detection using DeepForest (Jupyter Notebook) published in the Environmental Data Science book
Alejandro Coca-Castro, and Matt Allen. "Tree crown detection using DeepForest (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Feb 20 ,2022. https://w3id.org/ro-id/15d986da-2d7c-44fb-af71-700494485def.
Image showing interactive plot of bounding boxes and predictions using the deepforest model
Tree crown detection using DeepForest (Jupyter Notebook) published in the Environmental Data Science book.
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Department of Geography, University of Cambridge