Deep learning framework for detecting agroforestry regions in satellite imagery

Fuente: Zenodo
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Bibliographic Details
Main Author: Ortiz-Gonzalo, Daniel
Format: Recurso digital
Published: Zenodo 2025
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author Ortiz-Gonzalo, Daniel
author_facet Ortiz-Gonzalo, Daniel
contents <p>A state-of-the-art deep learning framework for detecting agroforestry regions in satellite imagery using dual-branch convolutional neural networks (CNN) with BigEarthNet pretrained features and forest loss data.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_16420669
institution Zenodo
language
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Deep learning framework for detecting agroforestry regions in satellite imagery
Ortiz-Gonzalo, Daniel
<p>A state-of-the-art deep learning framework for detecting agroforestry regions in satellite imagery using dual-branch convolutional neural networks (CNN) with BigEarthNet pretrained features and forest loss data.</p>
title Deep learning framework for detecting agroforestry regions in satellite imagery
url https://doi.org/10.5281/zenodo.16420669