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myst.yml
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# See docs at: https://mystmd.org/guide/frontmatter
version: 1
extends:
- https://raw.githubusercontent.com/eds-book/edsbook-config/main/edsbook.yml
project:
id: 15d986da-2d7c-44fb-af71-700494485def
title: Tree crown detection using DeepForest (Jupyter Notebook) published in the Environmental Data Science book
short_title: Tree crown (DeepForest)
abstract: Notebook developed to demonstrate how to detect tree crown using a state-of-art Deep Learning model for object detection.
authors:
- id: acoca
name: Alejandro Coca-Castro
orcid: 0000-0002-9264-1539
corresponding: true
email: acoca@turing.ac.uk
github: acocac
roles:
- Investigation
- Software
- Visualization
affiliations:
- turing
reviewers:
- id: malen
name: Matt Allen
github: mja2106
roles:
- Writing – review & editing
affiliations:
- cambridge
editors:
- acoca
affiliations:
- id: cambridge
name: University of Cambridge
- id: turing
name: The Alan Turing Institute
department: Environment & Sustainability
subject: Forest & Biomass
keywords:
- Forest & Biomass
- Modelling
- Standard
- Python
venue:
title: Environmental Data Science Book
short_title: EDS Book
url: https://www.edsbook.org
issue:
name: Standard
thumbnail: images/thumbnail.png
requirements:
- environment.yml
doi: 10.5281/zenodo.8309661
github: https://github.com/eds-book/15d986da-2d7c-44fb-af71-700494485def
jupyter:
binder:
repo: eds-book/15d986da-2d7c-44fb-af71-700494485def
open_access: true
license:
content: CC-BY-4.0
code: MIT
date: 2024-09-13
toc:
- file: README.md
- file: notebook.ipynb
exports:
- format: pdf
template: curvenote
article: notebook.ipynb
output: exports/notebook.pdf
- format: cff
type: software
version: v2025.6.0
license: MIT
license-url: https://opensource.org/license/MIT
identifiers:
- description: "Open review report for this notebook"
type: url
value: "https://github.com/alan-turing-institute/environmental-ds-book/pull/5"
bibliography:
- references.bib
site:
template: book-theme