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ZENODO
Software . 2025
License: http://opensource.org/licenses/MIT
Data sources: ZENODO
ZENODO
Software . 2025
License: https://opensource.org/licenses/MIT
Data sources: Datacite
ZENODO
Software . 2025
License: https://opensource.org/licenses/MIT
Data sources: Datacite
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Detecting floating objects using deep learning and Sentinel-2 imagery (Jupyter Notebook) published in the Environmental Data Science book

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 20 Jun 2025Publisher:Zenodo
Authors: Mifdal, Jamila; Carmo, Raquel;

doi: 10.5281/zenodo.8308843 , 10.5281/zenodo.15706997

Detecting floating objects using deep learning and Sentinel-2 imagery (Jupyter Notebook) published in the Environmental Data Science book

Abstract

Notebook developed to demonstrate the use of deep neural networks for the detection of floating objects on Sentinel-2 data.

Please cite the following works when using this project.

Keywords

Oceans, Modelling, Standard, Python

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
0
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