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Incidents Dataset.html
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Incidents Dataset.html
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<!doctype html>
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<title>Benchmark Datasets for Machine Learning for Natural Disasters</title>
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<h3><b>Detecting Natural Disasters, Damage, and Incidents in the Wild</b></h3> <!-- Title -->
<h5> Image | General | Preparedness </h5> <!-- Type | Topic | Disaster phase -->
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<div class="w3-container"> <!-- Data description -->
<p> Incidents Dataset is dataset for general disaster detection, and disaster classification. It contains 1,144,148 images (with 446,684 images as positives) and is introduced for multiclass classification.</p>
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<li class="list-group-item"><strong>ML task type:</strong> Multiclass classification</li>
<li class="list-group-item"><strong>Data Source:</strong> Google Images </li>
<li class="list-group-item"><strong>Size:</strong> 1,144,148 Images </li>
<li class="list-group-item"><strong>Timespan:</strong> N/A </li>
<li class="list-group-item"> <strong>Geographical Coverage:</strong> Global </li>
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<li class="list-group-item"> <strong>Baseline Information</strong></li>
<li class="list-group-item"> <strong>Evaluated on:</strong> CNN </li>
<li class="list-group-item"> <strong>Metrics used:</strong> Accuracy (Incident Classification); Average Precision (Incident Detection)</li>
<li class="list-group-item"> <strong>Results as reported in original paper: Accuracy: 77.3 (Incident Classification), mAP: 67.65 (Incident Detection)</strong> </li>
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<li class="list-group-item"> <strong>Find out more by:</strong></li>
<li class="list-group-item"> <a href="https://link.springer.com/chapter/10.1007/978-3-030-58529-7_20" target="_blank">Reading the research paper</a></li>
<li class="list-group-item"> <a href="https://github.com/ethanweber/IncidentsDataset" target="_blank">Checking out the dataset!</a></li>
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Ethan Weber, Nuria Marzo, Dim P Papadopoulos, Aritro Biswas, Agata Lapedriza, Ferda Ofli, Muhammad Imran, and
Antonio Torralba. Detecting natural disasters, damage, and incidents in the wild. In European Conference on Computer
Vision, pages 331–350. Springer, 2020.
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