Treffer: DeepTrees: Tree crown segmentation and analysis in remote sensing imagery with PyTorch

Title:
DeepTrees: Tree crown segmentation and analysis in remote sensing imagery with PyTorch
Authors:
Khan, Taimur, Arnold, C., Grover, H.
Source:
ISSN: 2475-9066.
Publisher Information:
Open Journals, Chicago, IL
Journal of Open Source Software 10 (114);; art. 8056
Publication Year:
2025
Subject Terms:
Deep Learning, Remote Sensing, Geospatial, Vegetation Ecology
Document Type:
Fachzeitschrift article in journal/newspaper
File Description:
application/pdf
Language:
English
Relation:
https://doi.org/10.5281/zenodo.17371394; https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=31576; https://dx.doi.org/10.21105/joss.08056
DOI:
10.21105/joss.08056
Availability:
https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=31576
https://doi.org/10.21105/joss.08056
Rights:
info:eu-repo/semantics/openAccess
Accession Number:
edsbas.67C0D4AE
Database:
BASE

Weitere Informationen

DeepTrees is a Python package for tree crown segmentation and analysis in remote sensing imagery. It uses PyTorch for training and predicting on large-scale datasets. Designed for direct integration with geospatial workflows, DeepTrees provides data loaders, transforms, and utility functions, enabling efficient experimentation in tree crown segmentation and tree traits analysis.