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4 results for “Floating Objects Detection”

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zenodo44/100

Outputs of the Jupyter Notebook - Detecting floating objects using Deep Learning and Sentinel-2 imagery

<p>The dataset contains the outputs of the notebook &quot;Detecting floating objects using Deep Learning and Sentinel-2 imagery&quot;&nbsp;published in the ocean modelling section of The Environmental Data Science Book.</p> <p><strong>Contributions</strong></p> <p><em>Notebook</em></p> <ul> <li> <p>Jamila Mifdal (author), European Space Agency &Phi;-lab,&nbsp;<a href="https://github.com/jmifdal">@jmifdal</a></p> </li> <li> <p>Raquel Carmo (author), European Space Agency &Phi;-lab,&nbsp;<a href="https://github.com/raquelcarmo">@raquelcarmo</a></p> </li> <li> <p>Alejandro Coca-Castro (reviewer), The Alan Turing Institute,&nbsp;<a href="https://github.com/acocac">@acocac</a></p> </li> </ul> <p><em>Modelling codebase</em></p> <ul> <li> <p>Jamila Mifdal (author), European Space Agency &Phi;-lab,&nbsp;<a href="https://github.com/jmifdal">@jmifdal</a></p> </li> <li> <p>Raquel Carmo (author), European Space Agency &Phi;-lab,&nbsp;<a href="https://github.com/raquelcarmo">@raquelcarmo</a></p> </li> <li> <p>Marc Ru&szlig;wurm (author), EPFL-ECEO,&nbsp;<a href="https://github.com/MarcCoru">@marccoru</a></p> </li> </ul>

opencc-by-4.0Jan 2022View details →
zenodo36/100

TUD-GV Dataset for Floating Litter Detection (object detection task)

<p>This dataset contains the data used for the publication:</p> <p>Jia, T., de Vries, R., Kapelan, Z., van Emmerik, T. H., &amp; Taormina, R. (2024). Detecting floating litter in freshwater bodies with semi-supervised deep learning.&nbsp;<em>Water Research</em>,&nbsp;<em>266</em>, 122405.</p> <p>This dataset is a subset of the large-scale "TU Delft - Green Village" (TUD-GV), which includes 9,473 RGB images. More details on the TUD-GV dataset can be found at:&nbsp;<a href="https://doi.org/10.5281/zenodo.7636124" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.7636124</a>. This subset used in this publication consists of 1,501 images, selected from the full TUD-GV dataset. All floating litter items in this subset have been annotated with bounding boxes. This subset is specifically for detecting floating litter in object detection tasks.</p> <p>The 1,501 images are stored in the <em>images.zip</em> file, the annotations are stored in the <em>labels_txt.zip</em> file, and the class of the annotation (i.e., litter) is stored in the <em>classes.txt</em> file.</p> <p>If you use this dataset for a publication, please cite the paper. Here is a BibTeX entry:</p> <pre>@article{jia2024detecting, title={Detecting floating litter in freshwater bodies with semi-supervised deep learning}, author={Jia, Tianlong and de Vries, Rinze and Kapelan, Zoran and van Emmerik, Tim HM and Taormina, Riccardo}, journal={Water Research}, volume={266}, pages={122405}, year={2024}, publisher={Elsevier} }</pre>

opencc-by-4.0Sep 2024View details →
zenodo28/100

Dataset of the Floating Objects Detection Notebook

<p>This dataset contains the data used in the notebook &quot;Detecting floating objects using Deep Learning and Sentinel-2 imagery&quot;, published in the ocean modelling section of The Environmental Data Science Book.</p>

opencc-by-4.0Jan 2022View details →
zenodo12/100

Dataset of the Floating Objects Detection Notebook

<p>This dataset contains the data used in the notebook &quot;Detecting floating objects using Deep Learning and Sentinel-2 imagery&quot;, published in&nbsp;the ocean modelling section of The Environmental Data Science Book.</p>

restrictedJan 2022View details →

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